Using train telematics data to provide information in one or more vehicles to reduce accident risk

ABSTRACT

A computer system configured to use train telematics data to reduce risk of accidents via a mobile device traveling within a vehicle may be provided. The mobile device may be configured to (1) receive train telematics data associated with a train that includes GPS location, speed, route, heading, acceleration, and/or track data; (2) determine when, or a time period of when, the train will pass through, be passing through, or be within a predetermined distance of a railroad crossing based upon the train telematics data; (3) determine an alternate route for the vehicle to take to avoid waiting at the railroad crossing; and (4) cause display of the alternate route on a display of the mobile device or a vehicle navigation system to allow the train to pass and to avoid train-vehicle collisions. Insurance discounts may be generated based upon the risk mitigation or prevention functionality.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims the benefit of, U.S.patent application Ser. No. 16/003,248, filed Jun. 8, 2018 and entitled“Using Train Telematics Data To Provide Information In One Or MoreVehicles To Reduce Accident Risk,” which is a continuation of and claimspriority to U.S. patent application Ser. No. 15/798,062 (now U.S. Pat.No. 10,054,453), entitled “Using Train Telematics Data To ProvideInformation In One Or More Vehicles To Reduce Accident Risk,” which wasfiled Oct. 30, 2017, which is a continuation of and claims priority toU.S. patent application Ser. No. 14/990,165, which is entitled “UsingTrain Telematics Data To Provide Information In One Or More Vehicles ToReduce Accident Risk,” which was filed Jan. 7, 2016 (now U.S. Pat. No.9,841,287), and which claims the benefit of (1) U.S. Provisional PatentApplication No. 62/105,468, entitled “Broadcasting Telematics Data ToNearby Mobile computing devices, Vehicles, And Infrastructure,” filedJan. 20, 2015, (2) U.S. Provisional Patent Application No. 62/113,749,entitled “Broadcasting Telematics Data To Nearby Mobile computingdevices, Vehicles, And Infrastructure,” filed Feb. 9, 2015, (3) U.S.Provisional Patent Application No. 62/204,749, entitled “BroadcastingTelematics Data To Nearby Mobile computing devices, Vehicles, AndInfrastructure,” filed Aug. 13, 2015, (4) U.S. Provisional PatentApplication No. 62/207,561, entitled “Generating Alert Notifications ByBroadcasting Telematics Data To Nearby Mobile computing devices,Vehicles, And infrastructure,” filed Aug. 20, 2015, (5) U.S. ProvisionalPatent Application No. 62/232,035 entitled “Generating AlertNotifications By Broadcasting Telematics Data To Nearby Mobile computingdevices, Vehicles, And Infrastructure,” filed. Sep. 24, 2015, (6) U.S.Provisional Patent Application No. 62/232,045, entitled “GeneratingAlert Notifications By Broadcasting Telematics Data To Nearby Mobilecomputing devices, Vehicles, And Infrastructure,” filed Sep. 24, 2015,(7) U.S. Provisional Patent Application No. 62/232,050, entitled“Determining Abnormal Traffic Conditions From A Broadcast Of TelematicsData Originating From Another Vehicle,” filed Sep. 24, 2015, (8) U.S.Provisional Patent Application No. 62/232,054, entitled “TakingCorrective Action Based Upon Telematics Data Broadcast From AnotherVehicle,” filed Sep. 24, 2015, (9) U.S. Provisional Patent ApplicationNo. 62/232,065, entitled “Analyzing Telematics Broadcast To DetermineTravel Events And Corrective Actions,” filed Sep. 24, 2015, (10) U.S.Provisional Patent Application No. 62/232,075, entitled “ProvidingInsurance Discounts Based Upon Usage Of Telematics Data-Based RiskMitigation And Prevention Functionality,” filed Sep. 24, 2015, (11) U.S.Provisional Patent Application No. 62/232,083, entitled “DeterminingCorrective Actions Based Upon Broadcast Of Telematics Data OriginatingFrom Another Vehicle,” filed. Sep. 24, 2015, (12) U.S. ProvisionalPatent Application No. 62/232,090, entitled “Determining CorrectiveActions Based Upon Telematics Data Broadcast From Another Vehicle,”filed Sep. 24, 2015, (13) U.S. Provisional Patent Application No.62/232,097, entitled “Generating Alert Notifications By BroadcastingTrain Telematics Data To Nearby Mobile computing devices, Vehicles, Andinfrastructure,” filed Sep. 24, 2015, (14) U.S. Provisional PatentApplication No. 62/247,334, entitled “Generating Alert Notifications ByBroadcasting Train Telematics Data To Nearby Mobile computing devices,Vehicles, And Infrastructure,” filed Oct. 28, 2015, and (15) U.S.Provisional Patent Application No. 62/250,286, entitled “GeneratingAlert Notifications By Broadcasting Train Telematics Data To NearbyMobile computing devices, Vehicles, And Infrastructure,” filed Nov. 3,2015. The disclosure of each of the aforementioned applications ishereby expressly incorporated by reference herein in its entirety.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to telematics data and, moreparticularly, to using telematics data to reduce risk of accidents.

BACKGROUND

Conventional telematics devices may collect certain types of data thatrelate to operation of a vehicle. However, conventional telematicsdevices and data gathering techniques may have several drawbacks.

BRIEF SUMMARY

In one aspect, telematics data and/or geographic location data may becollected, monitored, measured, and/or generated by one or morecomputing devices associated with a vehicle. In another aspect,telematics data and/or geographic location data may be collected,monitored, measured, and/or generated by one or more computing devicesassociated with a train. The telematics data may include various metricsthat indicate the direction, speed, and/or motion of the vehicle ortrain with which the data is associated. The geographic location datamay include a geographic location of the vehicle or train, such aslatitude and longitude coordinates, for example. The one or morecomputing devices may include a mobile computing device positionedwithin the vehicle or train, an on-board computer, a train controller(e.g., a smart train controller), and/or a combination of these devicesworking in conjunction with one another. The one or more computingdevices may broadcast the telematics data and/or the geographic locationdata to one or more other devices.

The telematics data and/or the geographic location data may be receivedand/or processed by one or more other computing devices to determinewhether an anomalous condition exists (e.g., whether a train is passingthrough, will pass through, or is within a predetermined distance of arailroad crossing such that travel of a vehicle through the railroadcrossing is affected). These one or more other computing devices may beexternal computing devices (e.g., a remote server), another mobilecomputing device, an infrastructure component (e.g., a railroadcrossing, which may be a “smart” railroad crossing as further discussedbelow), etc. If an anomalous condition is detected, the geographiclocation of the vehicle and/or train associated with the telematics datamay be used as a condition to decide whether to generate an alert at (orsend an alert notification to) one or more other computing devicesassociated with nearby vehicles.

In one aspect, a computer system configured to use train telematics datato reduce risk of accidents via a mobile device traveling within avehicle may be provided. A mobile device may include at least one of oneor more processors or transceivers. The at least one of the one or moreprocessors or the transceivers may be configured to: (1) receive, viawireless communication or data transmission, train telematics dataassociated with a train directly from a train transceiver or indirectlyfrom a railroad crossing, the train telematics data including at leastone of Global Positioning System (GPS) location, speed, route, heading,acceleration, or track data; (2) determine when, or a time period ofwhen, the train will pass through, be passing through, or be within apredetermined distance of the railroad crossing or another railroadcrossing based upon the train telematics data; (3) determine analternate route for the vehicle to take to avoid waiting at the railroadcrossing or the other railroad crossing to allow for the train to passunimpeded; and/or (4) cause the alternate route to be displayed on adisplay of the mobile device or a vehicle navigation system to allow thetrain to pass unimpeded and to facilitate avoidance of train-vehiclecollisions. The at least one of the one or more processors or thetransceivers may be configured to perform additional, fewer, oralternate actions, including those discussed elsewhere herein.

In another aspect, a computer-implemented method of using traintelematics data to reduce risk of accidents via a mobile devicetraveling within a vehicle may be provided. A method may include: (1)receiving, via at least one of one or more processors of the mobiledevice or associated transceivers via wireless communication or datatransmission, the train telematics data associated with a train directlyfrom a train transceiver or indirectly from a railroad crossing, thetrain telematics data including at least one of GPS location, speed,route, heading, acceleration, or track data; (2) determining, via theone or more processors of the mobile device based upon the traintelematics data, (i) when, or a time period of when, the train will passthrough or be passing through the railroad crossing or another railroadcrossing, or (ii) when the train is within a predetermined distance ofthe railroad crossing or the other railroad crossing; (3) determining,via the one or more processors of the mobile device, an alternate routefor the vehicle to take to avoid waiting at the railroad crossing or theother railroad crossing to allow for the train to pass; and/or (4)causing, via the one or more processors of the mobile device, thealternate route to be displayed on a display of the mobile device or avehicle navigation system to allow the train to pass unimpeded and tofacilitate avoidance of train-vehicle collisions. The method may includeadditional, fewer, or alternate actions, including those discussedelsewhere herein.

In yet another aspect, a computer-implemented method for utilizing traintelematics data may be provided. A method may include: (1) receiving, bya first mobile computing device located in a vehicle, the traintelematics data from a second mobile computing device located on atrain, the train telematics data including information indicative of atleast one of a speed, a heading, or a location of the train; (2)determining, by the first mobile computing device, at least one of aspeed, a location, or a route of the vehicle; (3) determining, by thefirst mobile computing device based upon a comparison between (i) the atleast one of the speed, the location, or the route of the vehicle, and(ii) the at least one of the speed, the heading, or the location of thetrain derived from the train telematics data, whether the vehicle willbe able to cross a railroad crossing before at least one of (i) acrossing signal associated with the railroad crossing is sounded or (ii)the train is within a threshold distance from the railroad crossing;and/or (4) issuing at least one of an audible alarm or a visual alarmwhen it is determined by the first mobile computing device that thevehicle will not be able to cross the railroad crossing before the atleast one of (i) the crossing signal is sounded or (ii) the train iswithin the threshold distance from the railroad crossing. The method mayinclude additional, fewer, or alternate actions, including thosediscussed elsewhere herein.

In another aspect, a computer-implemented method of using traintelematics data to reduce risk of collisions may be provided. The methodmay include (1) generating, via one or more processors (such as a smarttrain controller) or a Telematics App, train telematics data associatedwith movement of a train, the train telematics data including GPSlocation, speed, route, heading, acceleration, and/or track data; (2)determining, via the one or more processors, when the train is within apredetermined distance of a railroad crossing based upon the traintelematics data; and/or (3) when the train is determined to be withinthe predetermined distance of the railroad crossing and moving towardthe railroad crossing, broadcasting via the one or more processors (suchas via wireless communication or data transmission) an alert or thetrain telematics data (i) directly or indirectly to nearby autonomousvehicles to facilitate the autonomous vehicles avoiding or stopping atthe railroad crossing, or (ii) directly or indirectly to smart railroadcrossing infrastructure (e.g., a smart railroad crossing) to allowautomatic gate closing or other visual alerts at the railroad crossingto avoid train-vehicle collisions.

In another aspect, a computer-implemented method of using traintelematics data to reduce risk of collision may be provided. The methodmay include (1) generating, via one or more processors (such as a smarttrain controller) or a Telematics App, telematics data associated withmovement of a train, the train telematics data including GPS location,speed, route, heading, acceleration, and/or track data; (2) determining,via the one or more processors, a time period of when the train will bepassing through a railroad crossing based upon the train telematics data(such as based upon train GPS location, speed, heading, route, or trackinformation, and/or comparison with a GPS location of the railroadcrossing); and/or (3) when it is determined that the train is within thepredetermined distance of the railroad crossing and moving toward therailroad crossing, broadcasting via the one or more processors (such asvia wireless communication or data transmission): (a) the time period ofwhen the train will be passing through the railroad crossing, (b) analert, and/or (c) the train telematics data (i) directly or indirectlyto autonomous vehicles to facilitate the autonomous vehiclesautomatically avoiding (such as re-routing themselves based upon acurrent destination and the train telematics data) and/or automaticallystopping at the railroad crossing, or (ii) directly or indirectly tosmart railroad crossing infrastructure to allow automatic gate closingor generation of other visual alerts at the smart railroad crossing toavoid train-vehicle collisions.

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The Figures described below depict various aspects of the system andmethods disclosed therein. It should be understood that each Figuredepicts an embodiment of a particular aspect of the disclosed system andmethods, and that each of the Figures is intended to accord with apossible embodiment thereof. Further, wherever possible, the followingdescription refers to the reference numerals included in the followingFigures, in which features depicted in multiple Figures are designatedwith consistent reference numerals.

There are shown in the drawings arrangements which are presentlydiscussed, it being understood, however, that the present embodimentsare not limited to the precise arrangements and instrumentalities shown,wherein:

FIG. 1 illustrates a block diagram of an exemplary telematics collectionsystem 100 in accordance with an exemplary aspect of the presentdisclosure;

FIG. 2 illustrates a block diagram of an exemplary alert notificationsystem 200 in accordance with an exemplary aspect of the presentdisclosure;

FIG. 3 illustrates a block diagram of an exemplary computing device 300in accordance with an exemplary aspect of the present disclosure;

FIG. 4A illustrates an exemplary mobile computing device home screen 400in accordance with an exemplary aspect of the present disclosure;

FIG. 4B illustrates an exemplary mobile computing device applicationscreen 450 in accordance with an exemplary aspect of the presentdisclosure;

FIG. 5 illustrates a block diagram of an exemplary smart v e controlsystem 500 in accordance with an exemplary aspect of the presentdisclosure;

FIG. 6 illustrates an exemplary computer-implemented method 600 of usingtrain telematics data to reduce risk of accidents in accordance with anexemplary aspect of the present disclosure;

FIG. 7 illustrates an exemplary computer-implemented method 700 of usingtrain telematics data to reduce risk of accidents via a mobile devicetraveling within a vehicle in accordance with an exemplary aspect of thepresent disclosure; and

FIG. 8 illustrates an exemplary computer-implemented method 800 ofutilizing train telematics data in accordance with an exemplary aspectof the present disclosure.

The Figures depict preferred embodiments for purposes of illustrationonly. Alternative embodiments of the systems and methods illustratedherein may be employed without departing from the principles of theinvention described herein.

DETAILED DESCRIPTION

The present embodiments relate to, inter cilia, determining whether ananomalous condition associated with a train (e.g., that the train ispassing through, will pass through, or is within a predetermineddistance of a railroad crossing such that travel of a vehicle throughthe railroad crossing is affected) is detected at a location associatedwith a vehicle (e.g., a location of a railroad crossing for which travelof the vehicle therethrough is affected by the anomalous condition)using one or more computing devices within or otherwise associated withthe vehicle. If the detected anomalous condition may impact or affectanother vehicle on the road, embodiments are described to generateand/or send alert notifications to other vehicles that may be soaffected. In some aspects, the vehicle and/or the other vehicles may bean autonomous vehicle(s). As further described throughout thedisclosure, the process of detecting anomalous conditions and whetherthey apply to other vehicles may be performed through an analysis ofgeographic location data and/or telematics data broadcasted from one ormore computing devices within or otherwise associated with one or morerespective vehicles or the train.

The present embodiments may relate to collecting, transmitting, and/orreceiving telematics data; and may include a mobile device, avehicle-mounted processor, a train controller (e.g., a smart traincontroller), computer server, web pages, applications, software modules,user interfaces, interactive display screens, memory units, and/or otherelectronic, electrical, and/or wireless communication equipmentconfigured to provide the functionality discussed herein. As comparedwith the prior art, the present embodiments include specificallyconfigured computing equipment that provide for an enhanced method ofcollecting telematics and/or other vehicle/driving, conditions relateddata, and performing certain actions based upon the data collected.Using the telematics and/or other data collected, in conjunction withthe novel techniques discussed herein, recommendations and/ortravel/driving guidance may be provided to remote vehicles and/ordrivers.

The present embodiments may solve one or more technical problems relatedto (1) vehicle safety, and/or (2) vehicle navigation by using solutionsor improvements in another technological field, namely telematics.Vehicle safety and vehicle navigation is often impacted by short-termtraffic events that occur with little or no warning. For instance,vehicle accidents may be caused by road construction, other vehicleaccidents, traffic being temporarily re-routed, unexpected bad weather,other drivers or vehicles, a train passing through a railroad crossing,etc.

To address these and other problems, telematics data (and/or driverbehavior or vehicle information) may be captured in real-time, or nearreal-time, by a mobile device of a vehicle driver (or passenger) and/ora mobile device, train controller, etc. of a train. The mobile deviceand/or other device as described herein may be specifically configuredfor gathering, collecting, and/or generating telematics and/or otherdata as a vehicle and/or train is traveling.

For instance, the mobile device may be equipped with (i) various sensorsand/or meters capable of generating telematics data (Global PositioningSystem (GPS) unit, speed sensor, speedometer, odometer, gyroscope,compass, accelerometer, etc.) and/or (ii) an application, such as aTelematics Data Application or Telematics “App,” that includes computerinstructions and/or software modules stored in a non-transitory memoryunit that control collecting and generating telematics and/or otherdata. The mobile device and/or the application (or Telematics App) mayprovide a software module, user interface, and/or interactive displayscreen configured to facilitate the data collection. The mobile deviceand/or Telematics App executing thereon may be configured to prepare orotherwise format the telematics and/or other data collected or generatedfor transmission (via wireless communication and/or data transmission)to a mobile device of a second driver, a remote server, another (smart)vehicle, and/or an infrastructure component all of which may be equippedwith its own Telematics App or other telematics related applications.The Telematics App may include other functionality, including the mobiledevice functionality discussed elsewhere herein.

Alternatively, the mobile device may remotely access a web page, such asvia wireless communication with a remote server. The web page mayprovide the mobile device with the functionality to collect thetelematics and/or other data as the vehicle and/or train is moving.Additionally or alternatively, the web page may allow the mobile deviceto upload or transmit data in real-time, or near real-time, to a mobiledevice of a second driver, a remote server, an infrastructure component,and/or another (e.g., smart) vehicle.

Additionally or alternatively, a smart vehicle controller or processorand/or a smart train controller or processor may be configured with thesame functionality as that of the mobile device described above. Forinstance, a smart vehicle and/or train controller may include anapplication, software module, or computer instructions that provide forthe telematics and/or other data collection and generation functionalitydiscussed herein. The smart vehicle and/or train controller may be inwired or wireless communication with various (“smart” or “dumb”)vehicle-mounted and/or train-mounted meters, sensors, and/or detectors,such as speedometers, speed sensors, compasses, gyros, accelerometers,etc., that collect and/or generate telematics data and/or other datadetailing or associated with vehicle and/or train operation, and/ordriving or driver behavior.

In one aspect, by solving problems with collecting telematics dataand/or other data associated with driver behavior, vehicle operation orperformance, and/or train operation or performance, problems withvehicle navigation and/or vehicle operation may be resolved. Forinstance, telematics data associated with a first vehicle and/or a trainmay be collected in real-time by a mobile device of a first driverand/or a mobile device associated with the train. The mobile device(s)may be specifically configured to gather or generate telematics and/orother driver/vehicle/train data in real-time as the vehicle and/or trainis traveling, such as via a Telematics App running on the mobile device.If a traffic event is encountered, about to be encountered, and/orexpected or anticipated to be encountered by the vehicle as it travels(e.g., road construction; heavy traffic; congestion; bad weatherconditions; unlawful, unexpected or erratic operation of other vehicles;questionable or abnormal driving behavior of other drivers;irresponsible or overly aggressive drivers; un-attentive or tireddrivers; train passing through a railroad crossing, etc.), thetelematics (and/or data) data collected may indicate such.

The mobile device itself (and/or Telematics App) may be configured toidentify the type of traffic event and transmit the type of trafficevent to other mobile devices, a remote server, smart vehicles, and/oran infrastructure component. In one embodiment, the mobile device(and/or Telematics App) may be in wireless communication with a smartvehicle control system of the vehicle and/or a smart train controller orcontrol system of the train, and the smart vehicle control system and/orsmart train controller or control system may transmit the telematicsand/or other data, and/or any associated warnings, to a remote server,and/or roadside smart infrastructure or nearby mobile devices orvehicles of other drivers (such as to conserve battery power of themobile device).

Alternatively, the mobile device (and/or Telematics App) may transmitthe telematics and/or other data collected via wireless communicationand/or data transmission to a second computing device—such as a secondmobile device (of another driver), a second and smart vehicle, a remoteserver, and/or road side infrastructure (smart street signs or roadposts, smart toll booths, smart railroad crossings, etc.). After which,the second and remote computing device may analyze the telematics and/orother data that is collected in real-time, or near real-time, todetermine traffic events in real-time, or near real-time, respectively.Based upon the type and extent of traffic event detected, the secondcomputing device may issue warnings, determine recommendations, and/orre-route vehicles. For instance, the second computing device may cause adisplay screen or user interface of a mobile device or smart vehiclecontroller of remote drivers to display a map with (1) a current routethat the vehicle is on, (2) a virtual representation of the trafficevent, and/or (3) an alternate or recommended new route to an originaldestination that avoids the traffic event.

In one embodiment, a telematics application or software module (e.g.,the Telematics App as discussed herein) may be designed to communicatewith smart vehicles and smart infrastructure. An advantage of this isthat for a vehicle owner that does not have a “smart” vehicle withwireless communication technology, the application and/or softwaremodule deployed on a smart phone or other mobile device may communicatewith smart vehicles and infrastructure and/or remote servers and othermobile devices). The telematics application and/or software module maybe programmed to provide voice alerts: such as on a two lane road “donot pass-a vehicle is approaching” or “high speed vehicle is approachingto your left (or right);” “traffic light will turn in 10 seconds;” “turnleft to find an open parking space;” “traffic is stopped 1.5 milesahead;” “traffic has slowed to 20 mph 1.5 miles (or 2 blocks) ahead;”“recommended speed for turn ahead is 30 mph;” “ice on bridge (or ramp)ahead;” “train approaching,” “train approaching railroad crossing,”“train crossing for another 10 seconds,” “train approaching in 10seconds, stop at railroad crossing,” etc.

As an example, a first mobile device may be traveling in a vehicle. Thefirst mobile device may collect telematics data and/or other data, suchas via a telematics application running on one or more processorsmounted within the first mobile device. The first mobile device (and/orthe telematics application) may detect a travel event from the datacollected. For instance, the first mobile device (and/or the telematicsapplication executing thereon) may determine that the vehicle is locatedon the highway, but the vehicle is moving slower than the posted speedlimit; that both the vehicle and the train are approaching a railroadcrossing, etc. The first mobile device (and/or the telematicsapplication) may then transmit the data collected and/or an associatedmessage via wireless communication or data transmission to smartroadside infrastructure and/or nearby vehicles (or a second mobiledevice traveling within a nearby and second vehicle).

The second mobile device (and/or a telematics application runningthereon) may then, using the data received and/or message received fromthe first mobile device, generate an audible or visual warning or alertof the travel event, such as “Warning, congestion ahead,” “Warning,train approaching ahead,” “Train at railroad crossing,” “Train,” and/or“Recommend taking Exit 10 and traveling on Highway 12 for 5 miles untilExit 11 to avoid the congestion ahead.” The second mobile device (and/orassociated telematics application) may also be able to compare locationsof the travel event with the current location of the second vehicle todetermine if the travel event poses a potential obstacle to the secondvehicle reaching its destination without interruption. Thus, thetelematics data collected using a first mobile device (and/or atelematics application) and associated with a first driver may be usedto alert a second driver (associated with the second mobile device) of atravel event and/or re-route the second vehicle to facilitate safervehicle travel for the second driver and vehicle.

In one aspect, a mobile device (and/or the telematics application) maycompare a vehicle's traveling speed with a known posted speed limit. Ifthe vehicle's speed is below or above the posted speed by a certainthreshold, for example, 10 or 20 miles-per-hour, then the mobile devicemay generate a warning and transmit the warning to roadsideinfrastructure and/or nearby mobile devices or vehicles. For example,the message may state “Slow moving vehicle in right hand lane ahead;”“High speed vehicle approaching from rear;” And/or “High speed vehicleapproaching from ahead.”

Other messages or alerts that may be generated from mobile devices(and/or telematics applications executing thereon), smart vehiclecontrollers, smart train controllers, remote servers, and/or smartinfrastructure and transmitted to a mobile device of a driver (and/orsmart vehicle) may include “Construction 1 mile ahead;” “Rain (or Snow)5 miles ahead;” “Detour 2 blocks ahead,” “Traffic light directly aheadwill change from Green to Red starting in 5 seconds,” “Stranded vehicleon right side of road half a mile ahead;” “Recommend turning right atnext intersection to avoid travel event 3 blocks ahead,” “Trainapproaching ahead, stop at railroad crossing;” “Turn right to avoidwaiting for train to cross railroad crossing ahead,” “Train approachingrailroad crossing located 2 miles ahead,” “Train passing throughrailroad crossing ahead for another 30 seconds,” “Train passing throughrailroad crossing ahead in 5 minutes,” and/or other travel or trafficevent-related messages.

An insurance provider may collect data indicative of an insured's havingof and/or usage of the vehicle safety functionality provided herein(e.g., functionality associated with receiving a wireless communicationbroadcast including train telematics data, analyzing the traintelematics data, and directing corrective actions based upon the traintelematics data, as further discussed below). For instance, such datamay be collected at an insurance provider remote server and/or via amobile device application. Based upon an individual's usage and/ortaking travel recommendations, such as travel recommendations thatreduce or lower risk and/or enhance driver or vehicle safety, insurancepolicies (such as vehicle or life insurance policies) may be adjusted,generated, and/or updated. The insurance provider remote server maycalculate, update, and/or adjust insurance premiums, rates, discounts,points, programs, etc., such as adjusting an insurance discount orpremium based upon the insured having the functionality discussed hereinand/or the amount that the insured uses the functionality discussedherein. The updated insurance policies (and/or premiums, rates,discounts, etc.) may be communicated to insurance customers for theirreview, modification, and/or approval—such as via wireless communicationor data transmission from a remote server to a mobile device of theinsured (e.g., for display on a mobile device of the insured).

Telematics and Vehicle Navigation

In one aspect, by solving problems with collecting telematics dataand/or other data associated with driver behavior, vehicle operation orperformance, and/or train operation or performance, problems withvehicle navigation and/or vehicle operation may be resolved. Forinstance, telematics data associated with a first vehicle and/or a trainmay be collected in real-time by a mobile device of a first driverand/or a mobile computing device associated with the train. The mobiledevice(s) may be specifically configured to gather or generatetelematics and/or other driver/vehicle/train data in real-time as thevehicle and/or train is traveling. If a traffic event is encountered,about to be encountered, and/or expected or anticipated to beencountered by the vehicle as it travels (e.g., road construction; heavytraffic; congestion; bad weather conditions; unlawful, unexpected orerratic operation of other vehicles; questionable or abnormal drivingbehavior of other drivers; irresponsible or overly aggressive drivers;un-attentive or tired drivers; train passing through a railroadcrossing, etc.), the telematics (and/or data) data collected mayindicate such.

The mobile device itself may be configured to identify the type oftraffic event and transmit the type of traffic event to other mobiledevices, a remote server, smart vehicles, and/or an infrastructurecomponent. In one embodiment, the mobile device may be in wirelesscommunication with a smart vehicle control system of the vehicle and/ora smart train controller or control system of the train, and the smartvehicle control system and/or smart train controller or control systemmay transmit the telematics and/or other data, and/or any associatedwarnings, to a remote server, and/or roadside smart infrastructure ornearby mobile devices or vehicles of other drivers (such as to conservebattery power of the mobile device).

Additionally or alternatively, the mobile device may transmit thetelematics and/or other data collected via wireless communication and/ordata transmission to a second computing device—such as a second mobiledevice (of another driver), a second and smart vehicle, a remote server,and/or road side infrastructure (smart street signs or road posts, smarttoll booths, smart railroad crossings, etc.). After which, the secondand remote computing device may, analyze the telematics and/or otherdata that is collected in real-time, or near real-time, to determinetraffic events in real-time, or near real-time, respectively. Based uponthe type and extent of traffic event detected, the second computingdevice may issue warnings, determine recommendations, and/or re-routevehicles. For instance, the second computing device may cause a displayscreen or user interface of a mobile device or smart vehicle controllerof remote drivers to display a map with (1) a current route that thevehicle is on, (2) a virtual representation of the traffic event, and/or(3) an alternate or recommended new route to an original destinationthat avoids the traffic event.

Exemplary Telematics Collection System

FIG. 1 illustrates a block diagram of an exemplary telematics collectionsystem 100 in accordance with an exemplary aspect of the presentdisclosure. In some aspects, telematics collection system 100 mayinclude hardware and software applications configured to measure,calculate, generate, and/or collect geographic location data and/ortelematics data indicative of the speed, direction, and/or motion ofvehicle 108. Additionally or alternatively, telematics collection system100 may include hardware and software applications configured to receiveand process geographic location data and/or telematics data sent fromanother telematics collection system, to determine whether an anomalouscondition has been detected, whether to generate an alert, and/orwhether to send an alert notification. Telematics collection system 100may include various data communication channels for facilitating datacommunications between the various hardware and software componentsand/or communications with one or more external components.

In some aspects, telematics collection (e.g., one or more features oftelematics collection system 100) may additionally or alternatively beimplemented with respect to a train, such as train 210 discussed belowwith respect to FIG. 2. Thus, a train may include any one or moresuitable features of telematics collection system 100 as describedherein with respect to vehicle 108 so as to, for example, measure,calculate, generate, and/or collect geographic location data and/ortelematics data indicative of speed, direction, and/or motion of thetrain.

To accomplish this, telematics collection system 100 may include anysuitable number of computing devices, such as mobile computing device110 and/or on-board computing device 114, for example. These computingdevices may be disposed within vehicle 108, permanently installed invehicle 108, or removably installed in vehicle 108.

In the present aspects, mobile computing device 110 may be implementedas any suitable computing or mobile device (e.g., smartphone, tablet,laptop, wearable electronics, phablet, pager, personal digital assistant(PDA), smart glasses, smart watch or bracelet, etc.), while on-boardcomputer 114 may be implemented as a general-use on-board computer orprocessor(s) installed by the manufacturer of vehicle 108 or as anaftermarket modification to vehicle 108, for example. In variousaspects, mobile computing device 110 and/or on-board computer 114 may bea thin-client device configured to outsource any suitable portion ofprocessing via communications with one or more external components.

On-board computer 114 may supplement one or more functions performed bymobile computing device 110 described herein by, for example, sendinginformation to and/or receiving information from mobile computing device110. Mobile computing device 110 and/or on-board computer 114 maycommunicate with one or more external components via links 112 and 118,respectively. Additionally, mobile computing device 110 and on-boardcomputer 114 may, communicate with one another directly via link 116.

In one aspect, mobile computing device 110 may be configured withsuitable hardware and/or software (e.g., one or more applications,programs, files, etc.) to determine a geographic location of mobilecomputing device 110 and, hence, vehicle 108, in which it is positioned.Additionally or alternatively, mobile computing device 110 may beconfigured with suitable hardware and/or software to monitor, measure,generate, and/or collect one or more sensor metrics as part of thetelematics data. Mobile computing device 110 may be configured tobroadcast the geographic location data and/or the one or more sensormetrics to one or more external components.

In some aspects, the external components may include another mobilecomputing device substantially similar to or identical to mobilecomputing device 110. In accordance with such aspects, mobile computingdevice 110 may additionally or alternatively be configured to receivegeographic location data and/or sensor metrics broadcasted from anothermobile computing device, the details of which are further discussedbelow. Mobile computing device 110 may be configured to determine, uponreceiving the geographic location data and/or sensor metrics, whether ananomalous condition exists at the geographic location indicated by thegeographic location data. If so, mobile computing device 110 may beconfigured to generate one or more audio and/or video alerts indicativeof the determined anomalous condition.

On-board computer 114 may be configured to perform one or more functionsotherwise performed by mobile computing device 110. However, on-boardcomputer 114 may additionally be configured to obtain geographiclocation data and/or telematics data by communicating with one or morevehicle sensors that are integrated into vehicle 108. For example,on-board computer 114 may obtain geographic location data viacommunication with a vehicle-integrated global navigation satellitesystem (GNSS). To provide additional examples, on-board computer 114 mayobtain one or more metrics related to the speed, direction, and/ormotion of vehicle 108 via any number of suitable sensors, such asspeedometer sensors, braking sensors, airbag deployment sensors, crashdetection sensors, etc.

In one aspect, mobile computing device 110 and/or on-board computer 114may operate independently of one another to generate geographic locationdata and/or telematics data, to receive geographic location data and/ortelematics data broadcasted from another telematics collection system,to determine whether to generate one or more alerts, and/or to generateone or more alert notifications. In accordance with such aspects,telematics collection system 100 may include mobile computing device 110but not on-board computer 114, and vice-versa.

In other aspects, mobile computing device HO and/or on-board computer114 may operate in conjunction with one another to generate geographiclocation data and/or telematics data, to receive geographic locationdata and/or telematics data broadcasted from another telematicscollection system, to determine whether to generate one or more alerts,and to generate one or more alert notifications. In accordance with suchaspects, telematics collection system 100 may include both mobilecomputing device 110 and on-board computer 114. Mobile computing device110 and on-board computer 114 may share any suitable portion ofprocessing between one another to facilitate the functionality describedherein.

Upon receiving notification alerts from another telematics collectionsystem, aspects include telematics collection system 100 generatingalerts via any suitable audio, video, and/or tactile techniques. Forexample, alerts may be generated via a display implemented by mobilecomputing device 110 and/or on-board computer 114. To provide anotherexample, a tactile alert system 120 (e.g., a seat that can vibrate) maybe configured to generate tactile alerts to a vehicle operator 106 whencommanded by mobile computing device 110 and/or on-board computer 114.To provide another example, audible alerts may be generated via aspeaker 122, which may be part of vehicle 108's integrated speakersystem, for example.

Although telematics collection system 100 is shown in FIG. 1 asincluding one mobile computing device 110 and one on-board computer 114,various aspects include telematics collection system 100 implementingany suitable number of mobile computing devices 110 and/or on-boardcomputers 114.

Exemplary Telematics Alert Notification System

FIG. 2 illustrates a block diagram of an exemplary alert notificationsystem 200 in accordance with an exemplary aspect of the presentdisclosure. In one aspect, alert notification system 200 may include anetwork 201, N number of vehicles 202.1-202.N and respective mobilecomputing devices 204.1-204.N, an external computing device 206, aninfrastructure component 208, and/or a train 210. In one aspect, mobilecomputing devices 204 may be an implementation of mobile computingdevice 110, as shown in FIG. 1, while vehicles 202 may be animplementation of vehicle 108, also shown in FIG. 1. Each of vehicles202.1 and 202.2 may have an associated on-board computer, which is notshown in FIG. 2 for purposes of brevity, but may be an implementation ofon-board computer 114, as shown in FIG. 1. Additionally oralternatively, the train 210 may have an associated mobile computingdevice 212 (e.g., within train 210), which may be an implementation ofmobile computing device 110, and/or an associated on-board computer (notshown in FIG. 2), which may be an implementation of on-board computer114. Each of vehicles 202.1 and 202.2 may be configured for wirelessinter-vehicle communication and/or communication with one or more ofmobile computing devices 204.1-204.N, external computing device 206,infrastructure component 208, train 210, and/or mobile computing device212. Aspects include each of vehicles 202.1 and 202.2 being configuredto perform communications in any suitable manner, such as viavehicle-to-vehicle (V2V) wireless communication and/or other suitabledata transmission.

Although alert notification system 200 is shown in FIG. 2 as includingone network 201, two mobile computing devices 204.1 and 204.2, twovehicles 202.1 and 202.2, one external computing device 206, oneinfrastructure component 208, one train 210, and/or one mobile computingdevice 212, various aspects include alert notification system 200implementing any suitable number of networks 201, mobile computingdevices 204, vehicles 202, external computing devices 206,infrastructure components 208, trains 210, and/or mobile computingdevices 212. For example, alert notification system 200 may include aplurality of external computing devices 206 and more than two mobilecomputing devices 204, any suitable number of which being interconnecteddirectly to one another and/or via network 201.

In one aspect, each of mobile computing devices 204.1, 204.2, and 212may be configured to communicate with one another and/or any suitabledevice directly via peer-to-peer (P2P) wireless communication and/ordata transfer. In other aspects, each of mobile computing devices 204.1,204.2, and 212 may be configured to communicate indirectly with oneanother and/or any suitable device via communications over network 201,such as external computing device 206, infrastructure component 208,and/or train 210, for example. In still other aspects, each of mobilecomputing devices 204.1, 204.2, and 212 may be configured to communicatedirectly and indirectly with one another and/or any suitable device,which may be via concurrent communications or communications occurringat separate times.

Each of mobile computing devices 204.1, 204.2, and 212 may be configuredto send data to and/or receive data from one another and/or via network201 using one or more suitable communication protocols, which may be thesame communication protocols or different communication protocols as oneanother. To provide an example, mobile computing devices 204.1 and 204.2may be configured to communicate with one another via a direct radiolink 203 a, which may utilize, for example, a Wi-Fi direct protocol, anad-hoc cellular communication protocol, etc. Furthermore, mobilecomputing devices 204.1 and 204.2 may be configured to communicate withthe vehicle on-board computers located in vehicles 202.1 and 202.2,respectively, utilizing a BLUETOOTH communication protocol (radio linknot shown).

To provide additional examples, mobile computing devices 204.1 and 204.2may be configured to communicate with one another via radio links 203 band 203 c by each communicating with network 201 utilizing a cellularcommunication protocol. As an additional example, mobile computingdevices 204.1 and/or 204.2 may be configured to communicate withexternal computing device 206 via radio links 203 b, 203 c, and/or 203e. Still further, one or more of mobile computing devices 204.1 and/or204.2 may also be configured to communicate with one or more smartinfrastructure components 208 directly (e.g., via radio link 203 d)and/or indirectly (e.g., via radio links 203 c and 203 f via network201) using any suitable communication protocols.

To provide still further examples, mobile computing device 212 may beconfigured to communicate with mobile computing device 204.1 via adirect radio link 203 g; mobile computing device 212 may be configuredto communicate with mobile computing device 204.2 via a direct radiolink 203 h; mobile computing device 212 may be configured to communicatewith infrastructure component 208 via a direct radio link 203 i; andmobile computing device 212 may be configured to communicate withnetwork 201 via a radio link 203 j so as to allow mobile computingdevice 212 to communicate indirectly with any suitable component incommunication with network 201.

Mobile computing devices 204.1, 204.2, and 212 may be configured toexecute one or more algorithms, programs, applications, etc., todetermine a geographic location of each respective mobile computingdevice (and thus their associated vehicle or train) to generate,measure, monitor, and/or collect one or more sensor metrics astelematics data, to broadcast the geographic data and/or telematics datavia their respective radio links, to receive the geographic data and/ortelematics data via their respective radio links, to determine whetheran alert should be generated based upon the telematics data and/or thegeographic location data, to generate the one or more alerts, and/or tobroadcast one or more alert notifications.

Network 201 may be implemented as any suitable network configured tofacilitate communications between mobile computing devices 204.1, 204.2,and/or 212 and one or more of external computing device 206, smartinfrastructure component 208, or train 210. For example, network 201 mayinclude one or more telecommunication networks, nodes, and/or links usedto facilitate data exchanges between one or more devices, and mayfacilitate a connection to the Internet for devices configured tocommunicate with network 201. Network 201 may include any suitablenumber of interconnected network components that form an aggregatenetwork system, such as dedicated access lines, plain ordinary telephonelines, satellite links, cellular base stations, a public switchedtelephone network (PSTN), etc., or any suitable combination thereof.Network 201 may include, for example, a proprietary network, a secureelectronic communication network, a secure public internet, amobile-based network, a virtual private network, etc.

In aspects in which network 201 facilitates a connection to theInternet, data communications may take place over the network 201 viaone or more suitable Internet communication protocols. For example,network 201 may be implemented as a wireless telephony network (e.g.,GSM, CDMA, LTE, etc.), a Wi-Fi network (e.g., via one or more IEEE802.11 Standards), a WiMAX network, a Bluetooth network, etc. Thus,links 203 a-203 j may represent wired links, wireless links, or anysuitable combination thereof.

In aspects in which mobile computing devices 204.1, 204.2, and 212communicate directly with one another in a peer-to-peer fashion, network201 may be bypassed and thus communications between mobile computingdevices 204.1, 204.2, and 212 and external computing device 206 may beunnecessary. For example, in some aspects, mobile computing device 204.1or mobile computing device 212 may broadcast geographic location dataand/or telematics data directly to mobile computing device 204.2, Inthis case, mobile computing device 204.2 may operate independently ofnetwork 201 to determine whether an alert should be generated at mobilecomputing device 204.2 based upon the geographic location data and thetelematics data. In accordance with such aspects, network 201 andexternal computing device 206 may be omitted.

However, in other aspects, one or more of mobile computing devices204.1, 204.2, and/or 212 may work in conjunction with external computingdevice 206 to generate alerts. For example, in some aspects, mobilecomputing device 204.1 or mobile computing device 212 may broadcastgeographic location data and/or telematics data, which is received byexternal computing device 206. In this case, external computing device206 may be configured to determine whether an alert should be sent tomobile computing device 204.2 based upon the geographic location dataand the telematics data.

To provide an example, mobile computing device 204.1 or mobile computingdevice 212 may broadcast telematics data, which is received by mobilecomputing device 204.2 and/or vehicle 202.2. Upon receipt of thetelematics data, mobile computing device 204.2 and/or vehicle 202.2 maydetermine that an abnormal traffic condition (e.g., train passing orwill be passing through a railroad crossing (e.g., an implementation ofinfrastructure component 208)) exists at the location of the originatingvehicle (e.g., the location of mobile computing device 212 and train210) and/or whether this location is along a route traveled by vehicle202.2 or is otherwise relevant to vehicle 202.2.

Once this is determined, mobile computing device 204.2 and/or vehicle202.2 may automatically take a preventive or corrective action, whichmay include, for example, mobile computing device 204.2 and/or vehicle202.2 generating or determining an alert, issuing a visual alert,providing an audio or audible alert, identifying an alternate travelroute that avoids the location of the abnormal traffic condition,presenting an alternative travel route on a display or display screenfor use by a driver of vehicle 202.2, providing audio driving directionsfor the driver of vehicle 202.2 to travel along the alternate route,etc.

External computing device 206 may be configured to execute varioussoftware applications, algorithms, and/or other suitable programs.External computing device 206 may be implemented as any suitable type ofdevice to facilitate the functionality as described herein. For example,external computing device 206 may be implemented as a network server, aweb-server, a database server, one or more databases and/or storagedevices, a central monitoring system and/or dispatching center computerused by emergency response personnel, a railway monitoring system, orany suitable combination thereof. Although illustrated as a singledevice in FIG. 2, one or more portions of external computing device 206may be implemented as one or more storage devices that are physicallyco-located with external computing device 206, or as one or more storagedevices utilizing different storage locations as a shared databasestructure (e.g. cloud storage).

In some embodiments, external computing device 206 may be configured toperform any suitable portion of the processing functions remotely thathave been outsourced by one or more of mobile computing devices 204.1,204.2, and/or 212. For example, mobile computing device 204.1, 204.2,and/or 212 may collect data (e.g., geographic location data and/ortelematics data) as described herein, but may send the data to externalcomputing device 206 for remote processing instead of processing thedata locally. In such embodiments, external computing device 206 mayreceive and process the data to determine whether an anomalous conditionexists and, if so, whether to send an alert notification to, forexample, one or more of mobile computing devices 204.1 and/or 204.2.

In one aspect, external computing device 206 may additionally oralternatively be part of an insurer computing system (or facilitatecommunications with an insurer computer system), and as such may accessinsurer databases, execute algorithms, execute applications, accessremote servers, communicate with remote processors, etc., as needed toperform insurance-related functions. For example, external computingdevice 206 may facilitate the receipt of telematics data or other datafrom one or more mobile computing devices 204.1-204.N, which may beassociated with insurance customers and/or running a Telematics App, asfurther discussed below with reference to FIG. 3.

In aspects in which external computing device 206 facilitatescommunications with an insurer computing system (or is part of such asystem), data received from one or more mobile computing devices204.1-204.N may include logon credentials which may be verified byexternal computing device 206 or one or more other external computingdevices, servers, etc. These logon credentials may be associated with aninsurer profile, which may include, for example, insurance policynumbers, a description and/or listing of insured assets, vehicleidentification numbers of insured vehicles, addresses of insuredstructures, contact information, premium rates, discounts, etc.

In this way, data received from one or more mobile computing devices204.1-204.N may allow external computing device 206 to uniquely identifyeach insured customer and/or whether each identified insurance customerhas installed the Telematics App. Furthermore, any data collected fromone or more mobile computing devices 204.1-204.N may be referenced toeach insurance customer and/or any insurance policies associated witheach insurance customer for various insurance-related purposes.

For example, as further discussed below with reference to FIG. 3, theone or more mobile computing devices 204.1-204.N may broadcast, inaddition to or as part of the telematics data, data indicative ofwhether a Telematics App has been installed and/or usage data indicativeof how often a driver uses the Telematics App functionality whiledriving. Of course, similar or identical data may be received from avehicle as opposed to the mobile computing device located in thevehicle. That is, the same functions discussed below with reference toFIG. 3 regarding the Telematics App installed and executed on a mobilecomputing device may also (or alternatively) be installed and executedas part of a vehicle's integrated computer functions, as previouslydiscussed with reference to FIG. 1 above.

In various aspects, an insurer may leverage data regarding whether aninsured customer has installed a Telematics App or how often theTelematics App is used while driving to calculate, adjust, and/or updatevarious insurance pricing for an automotive insurance policy or othersuitable insurance policy. For example, as noted above, an insurer mayadjust insurance premiums, rates, discounts, points, programs, etc.,based upon the insured having the functionality discussed herein and/orthe amount that the insured uses the functionality discussed herein.

In addition, external computing device 206 may facilitate thecommunication of the updated insurance policies, premiums, rates,discounts, etc., to insurance customers for their review, modification,and/or approval—such as via wireless communication or data transmissionto one or more mobile computing devices 204.1-204.N. For example, aninsurer may provide an initial discount for an insured customerinstalling the Telematics App and logging in with the Telematics App. Tocontinue this example, because the alert notifications provided by theTelematics App may reduce the likelihood of a collision or other damageoccurring to the vehicle or the driver, use of the Telematics App mayfunction to mitigate or prevent driving risks upon which an insurancepolicy is partially based. Therefore, an insurer may provide anadditional discount that increases with the insured customer's usage ofthe Telematics App while driving.

In some aspects, external computing device 206 may facilitate indirectcommunications between one or more of mobile computing devices204.1-204.2, vehicles 202.1-202.N, infrastructure component 208, train210, and/or mobile computing device 212 via network 201 or anothersuitable communication network and/or wireless link. For example,external computing device 206 may receive telematics data from anoriginating mobile computing device 204.1 via radio link 203 b and relaythe telematics data to a destination mobile computing device 204.2and/or to vehicle 202.2 via radio link 203 c.

With respect to FIG. 2, infrastructure component 208 may be implementedas any suitable type of traffic infrastructure component configured toreceive communications from and/or to send communications to otherdevices, such as mobile computing devices 204.1, 204.2, and/or 212,and/or external computing device 206, for example.

In some aspects, as noted herein, infrastructure component 208 may beimplemented as one or more “smart” infrastructure components, which maybe configured to communicate with one or more other devices directlyand/or indirectly.

For example, smart infrastructure component 208 may be configured tocommunicate with one or more devices directly or indirectly. Forexample, smart infrastructure component 208 may be configured tocommunicate directly with mobile computing device 204.2 via link 203.dand/or with mobile computing device 204.1 via links 203 b and 203 futilizing network 201. To provide another example, smart infrastructurecomponent 208 may communicate with external computing device 206 vialinks 203 e and 203 f utilizing network 201.

Smart infrastructure component 208 may be implemented as any suitabletype of traffic infrastructure component configured to receivecommunications from and/or to send communications to other devices, suchas mobile computing devices 204.1, 204.2, and/or 212, and/or externalcomputing device 206, for example. For example, smart infrastructurecomponent 208 may be implemented as a traffic light, a railroad crossinglight, a construction notification sign, a roadside display configuredto display messages, a billboard display, etc.

Similar to external computing device 206, one or more smartinfrastructure components 208 may facilitate indirect communicationsbetween one or more of mobile computing devices 204.1-204.2, vehicles202.1-202.N, external computing device 206, train 210, and/or mobilecomputing device 212 via network 201 or another suitable communicationnetwork and/or wireless link. For example, one or more smartinfrastructure components 208 may receive telematics data from anoriginating mobile computing device 204.2 via radio link 203 d and relaythe telematics data to a destination mobile computing device 204.1and/or to vehicle 202.1 via radio links 203 b and 203 f.

When implemented as a railroad crossing, smart infrastructure component208 may be configured to detect when a train (e.g., train 210) isapproaching a railroad crossing in any suitable manner. For example, atraditional railroad crossing may cause a signal to be sounded, lightsto flash, gates to close, etc., upon an oncoming train approaching andtriggering a switch. Aspects include smart infrastructure component 208,however, detecting a train approaching from a distance that is furtherfrom the railroad crossing that would be detected by a typical railroadswitching system. This may be accomplished, for example, via thereceipt, processing, and/or analysis of train telematics data that istransmitted by a mobile device located in or otherwise associated with atrain and/or a dedicated device that is located in or otherwiseassociated with the train.

As explained above with respect to the telematics data corresponding toa vehicle, train telematics data may include metrics that indicate, forexample, the train's current geographic location, speed, heading,motion, etc. in various aspects, the train telematics data may becollected by a dedicated device located on the train and/or a mobiledevice located on the train, similar to the telematics collectionprocess discussed herein with respect to the vehicle telematics datacollected via mobile computing devices 204.1-204.N.

To provide a more particular example, in one aspect, the traintelematics data may include at least one of a timestamp, one or moresensor metrics indicative of braking motion of train 210, one or moresensor metrics indicative of acceleration motion of train 210, one ormore sensor metrics indicative of cornering motion of train 210, or oneor more sensor metrics indicative of a direction of train 210.

In another aspect, the train telematics data may additionally oralternatively include at least one of speed, acceleration, deceleration,GPS (Global Positioning System) coordinates (at times referred to hereinas “GPS location”), or lane data associated with train 210. In yetanother aspect, the train telematics data may additionally oralternatively include at least one of time, braking, acceleration, leftturn, right turn, heading, GPS speed, GPS latitude and longitude,gyroscope, battery level, or telephone usage data associated with train210. It should be appreciated that some of the train telematics dataassociated with train 210 may be associated with train 210 but be datathat is collected and/or gathered from one or more other devices and/orvehicles. For instance, telephone usage data associated with train 210may be telephone usage data of a mobile computing device in a vehicle,such as telephone usage data of mobile computing device 204.1 in vehicle202.1.

In some aspects, the train telematics data may also include informationrelevant to applications involving trains. For example, the traintelematics data may include a train number or other identifier, the typeof train (e.g., passenger vs. freight), a number of cars, an overalltrain length (which may be updated as additional cars are removed andadded via data received from external computing device 206 and/or userinteraction), an estimated time in which the train should reach arailroad crossing, an estimated time that it will take the train to passthrough a railroad crossing, etc.

In some aspects, smart infrastructure component 208 may be configured toreceive geographic location data and/or telematics data from one or moreother devices and to process this data to determine whether an anomalouscondition has been detected and whether the detected anomalous conditionsatisfies a threshold distance condition with respect to smartinfrastructure component 208. The threshold distance condition mayinclude, for example, the geographic location of the anomalous conditionbeing within a threshold radius of smart infrastructure component 208,on the same road serviced by smart infrastructure component 208, etc. ifso, smart infrastructure component 208 may perform one or more relevantactions such as displaying one or more relevant messages to notifydrivers in the vicinity, to modify traffic patterns, to change trafficlight timing, to redirect traffic, etc.

In other aspects, smart infrastructure component 208 may receive dataindicating that an alert is to be generated and/or the type of alertthat is to be generated. In accordance with such aspects, one or more ofmobile computing devices 204.1, 204.2 and/or external computing device206, for example, may make the determination of whether an anomalouscondition exists and is within a threshold distance of smartinfrastructure component 208. If so, the data received by smartinfrastructure component 208 may be indicative of the type of anomalouscondition, the location of the anomalous condition, commands to causesmart infrastructure component 208 to perform one or more acts, the typeof acts to perform, etc.

To provide some illustrative examples, a train (e.g., train 210) maybroadcast one or more signals indicating that the train is approaching arailroad crossing, which may be received by one or more of mobilecomputing devices 204.1-204.2 and/or smart infrastructure component 208and may result in the mobile computing devices generating one or morealert notifications and/or smart infrastructure component 208 changingto a different state. The broadcasted signal may be transmitted upon thetrain approaching (e.g., within a threshold distance of) the crossinglocation, and may be transmitted from a mobile device (e.g., mobilecomputing device 212) and/or equipment mounted on or otherwiseassociated with the train.

To provide another example, if smart infrastructure component 208 isimplemented as a smart traffic light, smart infrastructure component 208may change a traffic light from green to red (or vice-versa) or adjust atiming cycle to favor traffic in one direction over another. To provideyet another example, if smart infrastructure component 208 isimplemented as a traffic sign display, smart infrastructure component208 may display a warning message that the anomalous condition (e.g., atraffic accident) has been detected ahead and/or on a specific roadcorresponding to the geographic location data.

In additional aspects, other vehicles may play a role in the one or morealert notifications. To provide an illustrative example, an emergencyvehicle (e.g., an ambulance, fire truck, etc.) may be dispatched to thescene of an accident. In such a case, the emergency vehicle may beconfigured to broadcast one or more signals that cause one or more ofmobile computing devices 204.1-204.2 to generate one or more alertnotifications and/or smart infrastructure component 208 to change to adifferent state. These signals may be broadcasted from a mobilecomputing device carried by emergency response personnel and triggeredupon the vehicle approaching (e.g., within a threshold distance) ageographic location associated the vehicle accident. Additionally oralternatively, the signals may be broadcasted by any suitable devicemounted in or otherwise associated with the emergency response vehicle.

The signals transmitted from train 210 and/or additional vehicles suchas emergency response vehicles (emergency response vehicles not beingillustrated in FIG. 2 for purposes of brevity) may be transmitted inaccordance with any suitable communication protocol directly and/orindirectly to one or more or mobile computing devices 204.1-204.2 and/orsmart infrastructure component 208, for example. For example, thesignals may be transmitted directly to smart infrastructure component208, indirectly to one or more of mobile computing devices 204.1-204.2via network 201 and/or external computing device 206, etc.

Exemplary End-User/Destination Devices

The following details regarding the determination of an anomalouscondition are explained in this section with reference to computingdevice 300, which may be a mobile computing device or “mobile device”(e.g., smart phone, laptop, tablet, phablet, smart watch, wearableelectronics, etc). In the present aspect, computing device 300 may beimplemented as any suitable computing device, such as a mobile computingdevice (e.g., mobile computing device 110, as shown in FIG. 1). Inanother aspect, computing device 300 may be implemented as an on-boardvehicle computer (e.g., on-board vehicle computer 114, as shown in FIG.1). In still other aspects, computing device 300 may be implemented as adevice external to a vehicle (e.g., external computing device 206 orsmart infrastructure component 208, as shown in FIG. 2).

Depending upon the implementation of computing device 300, the methodsand processes utilized to determine the existence of anomalousconditions may be performed locally, remotely, or any suitablecombination of local and remote processing techniques.

FIG. 3 illustrates a block diagram of an exemplary computing device ormobile device 300 in accordance with an exemplary aspect of the presentdisclosure. Computing device 300 may be implemented as any suitablecomputing device configured to (1) monitor, measure, generate, and/orcollect telematics data; (2) broadcast the geographic location dataand/or the telematics data to one or more external components, such asvia wireless communication and/or data transmission; (3) receivegeographic location data and/or telematics data broadcasted from anotherdevice, such as via wireless communication and/or data transmission; (4)determine whether an anomalous condition exists at the geographiclocation indicated by the geographic location data based upon thetelematics data; (5) generate one or more alerts indicative of theanomalous condition; and/or (6) broadcast one or more alertnotifications to other devices, such as via wireless communicationand/or data transmission.

Computing device 300 may include a display 316, a graphics processingunit (GPU) 318, a location acquisition unit 320, a speaker/microphone322, a sensor array 326, a user interface 328, a communication unit 330,and/or a controller 340.

In one aspect, controller 340 may include a program memory 302, amicroprocessor (MP) 306, a random-access memory (RAM) 308, and/or aninput/output (I/O) interface 310, each of which may be interconnectedvia an address/data bus 312. Controller 340 may be implemented as anysuitable type and/or number of processors, such as a host processor forthe relevant device in which computing device 300 is implemented, forexample. In some aspects, controller 340 may be configured tocommunicate with additional data storage mechanisms that are not shownin FIG. 3 for purposes of brevity (e.g., one or more hard disk drives,optical storage drives, solid state storage devices, etc.) that residewithin or are otherwise associated with computing device 300.

Program memory 302 may store data used in conjunction with one or morefunctions performed by computing device 300 to facilitate theinteraction between computing device 300 and one or more other devices.For example, if computing device 300 is implemented as a mobilecomputing device (e.g., mobile computing device 204.1, as shown in FIG.2), then program memory 302 may store one or more programs,applications, algorithms, etc. that, when executed by controller 340,facilitate the interaction between mobile computing device 204.1 and (i)one or more networks (e.g., network 201), (ii) other mobile computingdevices (e.g., mobile computing device 204.2 and/or mobile computingdevice 212). (iii) external computing devices (e.g., external computingdevice 206), (iv) vehicles (e.g., vehicle 108), (v) vehicle on-boardcomputers (e.g., on-board computer 114), (vi) infrastructure components(e.g., smart infrastructure component 208), etc.

In various aspects, program memory 302 may be implemented as anon-transitory tangible computer readable media configured to storecomputer-readable instructions, that when executed by controller 340,cause controller 340 to perform various acts. Program memory 302 mayinclude an operating system 342, one or more software applications 344,and one or more software routines 352. To provide another example,program memory 302 may include other portions to store data that may beread from and written to by MP 306, such as data storage 360, forexample.

In one aspect, one or more MPs (micro-processors) 306 may be configuredto execute one or more of software applications 344, software routines352 residing in program memory 302, and/or other suitable softwareapplications. For example, operating system 342 may be implemented asany suitable operating system platform depending upon the particularimplementation of computing device 300. For example, if computing device300 is implemented as a mobile computing device, operating system 342may be implemented as a mobile OS platform such as the iOS®, Android™,Palm® webOS, Windows® Mobile/Phone, BlackBerry® OS, or Symbian® OSmobile technology platforms, developed by Apple Inc., Google Inc., PalmInc. (now Hewlett-Packard Company), Microsoft Corporation, Research inMotion (RIM), and Nokia, respectively.

In one embodiment, data storage 360 may store data such as applicationdata for the one or more software applications 344, routine data for theone or more software routines 352, geographic location data and/ortelematics data, etc.

Display 316 may be implemented as any suitable type of display and mayfacilitate user interaction with computing device 300 in conjunctionwith user interface 328. For example, display 316 may be implemented asa capacitive touch screen display, a resistive touch screen display,etc. In various embodiments, display 316 may be configured to work inconjunction with controller 340 and/or GPU 318 to display alerts and/ornotifications received from other devices indicative of detectedanomalous conditions.

Communication unit 330 may be configured to facilitate communicationsbetween computing device 300 and one or more other devices, such asother mobile computing devices, networks, external computing devices,smart infrastructure components, etc. As previously discussed withreference to FIGS. 1 and 2, computing device 300 may be configured tocommunicate with these other devices in accordance with any suitablenumber and type of communication protocols. Thus, in various aspects,communication unit 330 may be configured to support any suitable numberand type of communication protocols based upon a particular networkand/or device in which computing device 300 is communicating tofacilitate this functionality.

Communication unit 330 may be configured to support separate orconcurrent communications, which may be the same type of communicationprotocol or different types of communication protocols. For example,communication unit 330 may be configured to facilitate communicationsbetween computing device 300 and an external computing device (e.g.,external computing device 206) via cellular communications whilefacilitating communications between computing device 300 and the vehicleor train in which it is carried (e.g., vehicle 108 or train 210) via.BLUETOOTH communications.

Communication unit 330 may be configured to broadcast data and/or toreceive data in accordance with any suitable communications schedule.For example, communication unit 330 may be configured to broadcastgeographic location data and/or telematics data every 15 seconds, every30 seconds, every minute, etc. As will be further discussed below, thegeographic location data and/or telematics data may be sampled inaccordance with any suitable sampling period. Thus, when broadcasted bycommunications unit 330 in accordance with a recurring schedule, thegeographic location data and/or telematics data may include a log orcollection of the geographic location data and/or telematics data thatwas sampled since the last data transmission. A suitable communicationschedule may be selected as a tradeoff between a desired anomalouscondition detection speed and battery usage of computing device 300,when applicable.

Additionally or alternatively, aspects include communication unit 330being configured to conditionally send data, which may be particularlyadvantageous when computing device 300 is implemented as a mobilecomputing device, as such conditions may help reduce power usage andprolong battery life. For example, communication unit 330 may beconfigured to only broadcast when telematics data has been sampled sincethe last transmission, which will be further discussed below withregards to sensor array 326. Controller 340 may determine whether hasbeen sampled since the last transmission by, for example, analyzing amemory address range (e.g., in data storage 360, RAM 308, etc.)associated with the storage of the telematics data and comparing thecontents of this buffer to a known range of valid values.

To provide another example, aspects include communication unit 330 beingadditionally or alternatively configured to only broadcast telematicsdata when computing device 300 is connected to a power source (e.g., anin-vehicle or in-train charger). To provide still another example,aspects include communication unit 330 being additionally oralternatively, configured to only broadcast telematics data whencommunication unit 330 is connected to and/or communicating with adevice identified as a vehicle. This may include, for example,identifying a BLUETOOTH connection as a valid vehicle to satisfy thiscondition upon installation and/or setup of the relevant application orprogram executed by computing device 300 to facilitate the functionalitydescribed herein.

Location acquisition unit 320 may be configured to generate geographiclocation data utilizing any suitable global positioning techniques. Forexample, location acquisition unit 320 may communicate with one or moresatellites and/or wireless transmitters to determine a location ofcomputing device 300. Location acquisition unit 320 may use “AssistedGlobal Positioning System” (A-GPS), satellite GPS, or any other suitableglobal positioning protocol (e.g., the GLONASS system operated by theRussian government, the Galileo system operated by the European Union,etc.) to determine a geographic location of computing device 300.

In one aspect, location acquisition unit 320 may periodically store oneor more geographic locations of computing device 300 as geographiclocation data in any suitable portion of memory utilized by computingdevice 300 (e.g., program memory 302, RAM 308, etc.) and/or to anotherdevice (e.g., another mobile computing device, an external computingdevice, etc.). In this way, location acquisition unit 32.0 may samplethe location of computing device 300 in accordance with any suitablesampling rate (e.g., every 5 seconds, 10 seconds, 30 seconds, etc.) andstore this geographic location data representing the position ofcomputing device 300, and thus the vehicle or train in which it istravelling, over time.

Speaker/microphone 322 may be configured as one or more separatedevices. Speaker/microphone 322 may include a microphone configured todetect sounds and to convert sounds to data suitable for communicationsvia communications unit 330. Speaker/microphone 322 may additionally oralternatively include a speaker configured to play sound in response todata received from one or more components of computing device 300 (e.g.,controller 340). In one embodiment, speaker/microphone 322 may beconfigured to play audible alerts.

User-interface 328 may be implemented as any suitable device configuredto collect user input, such as a “soft” keyboard displayed on display316 of computing device 300, a keyboard attached to computing device300, an external keyboard communicating via a wired or a wirelessconnection (e.g., a BLUETOOTH keyboard), an external mouse, etc.

Sensor array 326 may be configured to measure any suitable number and/ortype of sensor metrics as part of the telematics data. In one aspect,sensor array 326 may be implemented as one or more sensors positioned todetermine the speed, force, heading, direction, and/or any othersuitable metric(s) (e.g., any other suitable metric(s) corresponding toone or more examples of train telematics data discussed above)associated with movements of computing device 300 and, thus, a vehicleor train in which computing device 300 is positioned. Additionally oralternatively, sensor array 32.6 may be configured to communicate withone or more portions of computing device 300 to measure, collect, and/orgenerate one or more sensor metrics from one or more non-sensor sources,which will be further discussed below. Generally speaking, any suitablemetric(s) and/or other indications corresponding to one or more examplesof train telematics data discussed herein may be measured, collected,and/or generated.

To generate one or more sensor metrics, sensor array 326 may include,for example, one or more cameras, accelerometers, gyroscopes,magnetometers, barometers, thermometers, proximity sensors, lightsensors, Hall Effect sensors, etc. In aspects in which sensor array 326includes one or more accelerometers, sensor array 326 may be configuredto measure and/or collect accelerometer metric values utilizing anX-axis, Y-axis, and Z-axis accelerometer. In accordance with suchaspects, sensor array 326 may measure sensor metric values as athree-dimensional accelerometer vector that represents the movement ofcomputing device 300 in three dimensional space by combining the outputsof the X-axis, Y-axis, and Z-axis accelerometers using any suitabletechniques.

In one aspect, sensor array 326 may include one or more cameras or otherimage capture devices. In accordance with such aspects, the one or morecameras that are part of sensor array 326 may be mounted or otherwisepositioned on computing device 300 such that, when computing device 300(e.g., a mobile computing device) is docked, cradled, or otherwisemounted within a vehicle or train, images may be captured from thisvantage point. For example, when computing device 300 is mounted withina vehicle, a camera implemented by sensor array 326 may function as adashboard camera, capturing images and/or video data of various objectsoutside of the vehicle from this vantage point. Additionally oralternatively, computing device 300 may capture audio data with theimage and/or video data via speaker/microphone 322.

In various aspects, computing device 300 may begin to capture data upondetecting that it has been placed in a cradle, and otherwise not capturedata in such a manner. This detection may occur, for example, via one ormore conditions being satisfied. For example, computing device 300 mayutilize one or more sensors (e.g., an accelerometer that is part ofsensor array 326) to determine that computing device 300 has changedorientation to horizontal (as is common when docked), that computingdevice 300 is communicating via BLUETOOTH with the vehicle or train,that the vehicle or train is moving above a threshold speed, etc.Aspects include any suitable number of conditions, upon being satisfied,triggering computing device 300 to start collecting telematics data,images, audio, video, etc., via sensor array 326.

In various aspects, sensor array 326 may be configured to sample the oneor more sensor metrics in accordance with any suitable sampling rateand/or based upon one or more conditions being satisfied. For example,sensor array 326 may be configured to implement one or moreaccelerometers to sample sensor metrics indicative of a g-forceassociated with vehicle or train braking, acceleration, and cornering ata rate of 15 Hz, 30 Hz, 60 Hz, etc., which may be the same sampling rateas one another or different sampling rates. To provide another example,sensor array 326 may be configured to implement one or more gyroscopesto improve the accuracy of the measured one or more sensor metrics andto determine whether computing device 300 is in use or stationary withina vehicle or train. To provide another example, sensor array 326 mayimplement a compass (magnetometer) to determine a direction or headingof a vehicle or train in which computing device 300 is located.

Again, sensor array 326 may additionally or alternatively communicatewith other portions of computing device 300 to obtain one or more sensormetrics even though these sensor metrics may not be measured by one ormore sensors that are part of sensor array 326. For example, sensorarray 326 may communicate with one or more of location acquisition unit320, communication unit 330, and/or controller 340 to obtain data suchas timestamps synchronized to the sampling of one or more sensor metrics(which may be measured to within hundredths of a second or smallerresolutions), geographic location data (and correlated timestampsthereof), a velocity based upon changes in the geographic location dataover time, a battery level of computing device 300, whether a battery ofcomputing device 300 is charging, whether computing device 300 is beinghandled or otherwise in use, an operating status of computing device 300(e.g., whether computing device 300 is unlocked and thus in use).

In various aspects, sensor array 326 may base timestamps upon anysuitable clock source, such as one utilized by location acquisition unit320 for GNSS functions. The timestamps may be, for example, recorded orlogged as various data is sampled to be synchronized to the sampling ofone or more sensor metrics (which may be measured to within hundredthsof a second or smaller resolutions).

Additionally or alternatively, sensor array 326, location acquisitionunit 320, and/or communication unit 330 may log or otherwise measurevarious metrics or other data that may be used by controller 340 todetermine how often the functionality of the Telematics Application isbeing utilized when a vehicle or train is being driven. For example,sensor array 326 may log the time when telematics data is beingcollected, when the Telematics Application is running, and/or when theTelematics Application has been started. To provide additional examples,communication unit 330 may store data indicative of a BLUETOOTHconnection status of computing device 300. To provide yet anotherexample, location acquisition unit 320 may store and/or log the changesin geographic location of computing device 300 over time.

In various aspects, controller 340 may determine how often a driver usesthe Telematics App based upon any suitable combination of theaforementioned data. For example, the BLUETOOTH connection status may beleveraged to determine whether computing device 300 is located in avehicle. To provide another example, the changes in the geographiclocation data over time may be utilized to determine whether computingdevice 300 has exceeded a threshold speed for a threshold duration oftime. In this way, a determination may be made whether computing device300 is located in a vehicle while the vehicle is being driven.

Various aspects include the aforementioned data being leveraged tocalculate a usage amount in which a user utilizes the Telematics Appwhile driving. For example, the usage amount may be based upon a totalproportion of time (e.g., 80% of the time while driving, thefunctionality provided by the Telematics App is enabled). To provideanother example, the usage amount may be mileage-based (e.g., 90% of themiles driven are done so with the functionality of the Telematics Appavailable to the driver). As discussed above, this usage data may besent to an insurer or other third party via a telematics datatransmission or a separate transmission and used to set and/or adjust aninsurance policy, premium, or discount for the insured customer.

In one aspect, sensor array 326 may sample one or more sensor metricsbased upon one or more conditions being satisfied. For example, sensorarray 326 may determine, based upon gyroscope sensor metrics,communication with controller 340, etc., whether computing device 300 isin use. If computing device 300 is in use (e.g., when implemented as amobile computing device) then the movement of computing device 300within the vehicle or train may not truly represent the vehicle or trainmotion, thereby causing sensor metrics sampled during this time to beerroneous. Therefore, aspects include sensor array 326 sampling the oneor more sensor metrics when computing device 300 is not in use, andotherwise not sampling the one or more sensor metrics.

In one aspect, sensory array 326 may include one or more cameras and/orimage capture devices. When sensory array 326 is implemented with one ormore cameras, these cameras may be configured as any suitable type ofcamera configured to capture and/or store images and/or video. Forexample, when computing device 300 is mounted in a vehicle or train, thecamera may be configured to store images and/or video data of the roador track in front of the vehicle or train in which it is mounted, and tostore this data to any suitable portion of program memory 302 (e.g.,data storage 360). Controller 340 and/or MP 306 may analyze this data togenerate one or more local alerts, to transmit signals indicative ofdetected alerts to one or more other devices, etc., which is furtherdiscussed below with reference to the execution of anomalous conditiondetection routine 358.

Again, the telematics data broadcasted by computing device 300 mayinclude one or more sensor metrics. However, the telematics data mayadditionally or alternatively include other external data that may berelevant in determining the presence of an anomalous condition. Forexample, the telematics data may include external data such as speedlimit data correlated to a road upon which computing device 300 islocated (and thus the vehicle in which it is travelling), an indicationof a type of road, a population density corresponding to the geographiclocation data, etc.

In some aspects, computing device 300 may obtain this external data byreferencing the geographic location data to locally stored data (e.g.,data stored in data storage 360) and broadcasting this data appended toor otherwise included with the sensor metrics data as part of thetelematics data. In other aspects, the device receiving the telematicsdata (e.g., a mobile computing device, an external computing device, aninfrastructure component) may generate the external data locally or viacommunications with yet another device. As will be further discussedbelow, this external data may further assist the determination ofwhether an anomalous condition is present.

In some aspects, software applications 344 and/or software routines 352may reside in program memory 302 as default applications that may bebundled together with the OS of computing device 300. For example, webbrowser 348 may be part of software applications 344 that are includedwith OS 342 implemented by computing device 300.

In other aspects, software applications 344 and/or software routines 352may be installed on computing device 300 as one or more downloads, suchas an executable package installation file downloaded from a suitableapplication store via a connection to the Internet. For example, alertnotification application 346, telematics collection routine 354,geographic location determination routine 356, and/or anomalouscondition detection routine 358 may be stored to suitable portions ofprogram memory 302 upon installation of a package file downloaded insuch a manner. Examples of package download files may include downloadsvia the iTunes store, the Google Play Store, the Windows Phone Store,downloading a package installation file from another computing device,etc. Once downloaded, alert notification application 346 may beinstalled on computing device 300 as part of an installation packagesuch that, upon installation of alert notification application 346,telematics collection routine 354, geographic location determinationroutine 356, and/or anomalous condition detection routine 358 may alsobe installed.

In one embodiment, software applications 344 may include an alertnotification application 346, which may be implemented as a series ofmachine-readable instructions for performing the various tasksassociated with executing one or more embodiments described herein. Inone aspect, alert notification application 346 may cooperate with one ormore other hardware or software portions of computing device 300 tofacilitate these functions.

In one aspect, alert notification application 346 may function as aTelematics Application (or “App”) which is downloaded and installed oncomputing device (or mobile device) 300 by a user via a suitablethird-party software store and/or portal (e.g., Apple iTunes, GooglePlay, the Windows Store, etc.).

To provide an illustrative example, software applications 344 mayinclude instructions for performing tasks such as determining ageographic location of computing device 300 (e.g., via communicationswith location acquisition unit 320), monitoring, measuring, generating,and/or collecting telematics data, broadcasting the geographic locationdata and/or the telematics data to one or more external devices,receiving geographic location data and/or telematics data from anothercomputing device, determining whether an anomalous condition existsbased upon the geographic location data and/or the telematics data,generating one or more alerts indicative of the determined anomalouscondition, receiving user input, facilitating communications betweencomputing device 300 and one or more other devices in conjunction withcommunication unit 330, etc.

Software applications 344 may include a web browser 348. In someembodiments (e.g., when computing device 300 is implemented as a mobilecomputing device), web browser 348 may be a native web browserapplication, such as Apple's Safari®, Google Android™ mobile webbrowser, Microsoft Internet Explorer® for Mobile, Opera Mobile™, etc. Inother embodiments, web browser 348 may be implemented as an embedded webbrowser.

Regardless of the implementation of web browser 348, various aspectsinclude web browser 348 being implemented as a series ofmachine-readable instructions for interpreting and displaying web pageinformation received from an external computing device (e.g., externalcomputing device 206, as shown in FIG. 2). This web page information maybe utilized in conjunction with alert notification application 346 toperform one or more functions of the aspects as described herein.

In one embodiment, software routines 352 may include a telematicscollection routine 354. Telematics collection routine 354 may includeinstructions, that when executed by controller 340, facilitate sampling,monitoring, measuring, collecting, quantifying, storing, encrypting,transmitting, and/or broadcasting of telematics data (e.g., traintelematics data such as the train telematics data described in greaterdetail herein). In some aspects, telematics collection routine 354 mayfacilitate collection of telematics data locally via one or morecomponents of computing device 300 (e.g., via sensor array 326, locationacquisition unit 320, controller 340, etc.). In other aspects,telematics collection routine 354 may facilitate the storage oftelematics data received from another device (e.g., via communicationunit 330).

In one aspect, telematics collection routine 354 may work in conjunctionwith controller 340 and/or alert notification application 346 toperiodically listen for and/or to periodically broadcast telematicsdata. For example, controller 340 may, upon executing alert notificationapplication 346, periodically listen for a broadcast containingtelematics data generated and transmitted from other computing devices,vehicles, trains, external computing devices, and/or smartinfrastructure components. Upon detecting a broadcast, controller 340may download the broadcast to a suitable portion of program memory 302and analyze the telematics data contained therein for potential trafficevents, travel events, one or more trains passing through one or morerailroad crossings, alerts, messages, etc. Such aspects may beparticularly useful, for example, to save battery life of the computingdevice, as continuous listening is not necessary but instead may beperformed, for example, in accordance with a particular timing schedule.

To provide another example, controller 340 may, upon executing alertnotification application 346, periodically broadcast telematics data,which may be received by other computing devices, vehicles, trains,external computing devices, and/or smart infrastructure components.

In one embodiment, software routines 352 may include a geographiclocation determination routine 356. Geographic location determinationroutine 356 may include instructions, that when executed by controller340, facilitate sampling, measuring, collecting, quantifying, storing,transmitting, and/or broadcasting of geographic location data (e.g.,latitude and longitude coordinates of a train (e.g., train 210)). Insome aspects, geographic location determination routine 356 mayfacilitate generating and/or storing geographic location data locallyvia one or more components of computing device 300 (e.g., via locationacquisition unit 320 and/or communication unit 330). In some aspects,geographic location determination routine 356 may additionally oralternatively facilitate the storage of geographic location datareceived from another device (e.g., via communication unit 330).

Additionally or alternatively, software routines 352 may includeanomalous condition detection routine 358. Anomalous condition detectionroutine 358 may include instructions, that when executed by controller340, facilitate the determination of whether an anomalous conditionexists (e.g., a train passing through a railroad crossing) based uponthe telematics data, the geographic location data, and/or image and/orvideo data captured by one or more cameras or other imaging devices. Ananomalous condition may include any suitable condition that indicates adeviation from normal traffic patterns, including the ability of avehicle(s) to drive over or through a railroad crossing without waitingfor a train to pass. For example, if an accident occurs, traffic mayslow down due to a car pileup, a reduction in available lanes, and/orrerouting of traffic. Because the telematics data may include dataindicative of the speed limit at the location corresponding to thegeographic location where the telematics data was sampled, a comparisonbetween the speed of computing device 300 and the posted or other speedlimit data (such as a comparison between mobile device or vehicle speedwith a map of, and/or known, posted speed limit information) mayindicate an anomalous condition. In an aspect where determining whetheran anomalous condition exists includes determining whether a train ispassing (or will pass, etc.) through a railroad crossing, the speed ofcomputing device 300 may be or may be included within the traintelematics data. Furthermore, because each vehicle and/or train maysample and/or broadcast geographic location data and/or telematics datain real time, the anomalous conditions may be detected with minimaldelay as they occur.

Although the speed of the vehicle and/or train may indicate an anomalouscondition, aspects include other types of anomalous conditions beingdetected based upon the telematics data. For example, an anomalouscondition may be identified when the one or more sensor metrics indicatethat an airbag has been deployed, and thus the vehicle associated withcomputing device 300 has been in an accident. This may be determined,for example, via an analysis of barometer readings matching a pressureversus time profile and/or via an indication from a dedicated airbagdeployment sensor located in the vehicle.

To provide another example, an anomalous condition may be identifiedbased upon weather fluctuations associated with a rapid formation ofice, a sudden change from a paved to a dirt road, the triggering of acrash detection system, a threshold number of wheel slips and/or skidsbeing sampled within a threshold sampling period (indicating slipperyconditions), sensor metrics indicative of a rollover condition, a suddenstop (indicating a collision), a departure from the road (indicating apulled over vehicle), etc.

To provide an illustrative example based upon a train passing through arailroad crossing, mobile computing device 212 (which may be animplementation of computing device 300) may determine that a geographiclocation of train 210 is within a predetermined or threshold distance ofsmart infrastructure component 208 implemented as a railroad crossing(e.g., a smart railroad crossing). Mobile computing device 212 may, uponexecution of anomalous condition detection routine 358, conclude thattrain 210 will pass through the railroad crossing at a particular timebased upon, for example, speed, acceleration, and/or any other suitablemetrics and/or data that may be included in the train telematics data asdiscussed herein. Upon determination of the anomalous condition, alertnotification application 346 may broadcast a notification indicating thedetected anomalous condition, the telematics data, and/or the geographiclocation data associated with the detected anomalous condition.

One or more vehicles (e.g., vehicle 202.1 and/or vehicle 202.2) may beequipped with additional computing devices 300 (e.g., implemented asmobile computing device 204.1 and/or mobile computing device 204.2), andmay receive this data and determine whether the anomalous condition isrelevant to the respective vehicle(s) based upon, for example, thegeographic relationship between the vehicle(s) and train 210, and/orbased upon other train telematics data. If the anomalous condition isrelevant, then mobile computing device 204.1 and/or mobile computingdevice 204.2, for example, may generate an alert(s) indicating theanomalous condition. For instance, the alert(s) may include directingthe driver(s) of the respective vehicle(s) and/or directing therespective autonomous vehicle(s) to travel along an alternate route(s),to stop at the railroad crossing that train 210 will pass through (or ispassing through), and/or to stop at another railroad crossing(s). Theother railroad crossing(s) may be, for instance, other railroadcrossing(s) near the railroad crossing that train 210 will pass throughand that is/are along the route(s) currently being traveled by thevehicle(s) or autonomous vehicle(s)).

In another aspect, the notification indicating the detected anomalouscondition may not be broadcast, and mobile computing device 204.1 and/or204.2, for example, may receive the telematics data and/or thegeographic location data and determine whether an anomalous conditionexists that is relevant to the respective vehicle(s) based upon thisreceived data. If the anomalous condition is relevant, then mobilecomputing device 204.1 and/or mobile computing device 204.2, forexample, may generate an alert as described above. It should beappreciated that in the foregoing examples directed to a train passingthrough a railroad crossing, train telematics data may be received, forinstance, directly from a train transceiver (which may be a transceiverof mobile computing device 212, a transceiver of a dedicated device thatis located in or otherwise associated with train 210 and that transmitstrain telematics data, etc.) or indirectly from a smart railroadcrossing. As noted above, the smart railroad crossing may be animplementation of smart infrastructure component 208.

To provide an illustrative example based upon a traffic accident, if afirst vehicle carrying a first computing device 300 is slowed down dueto a traffic accident, then the one or more sensor metrics sampled bysensor array 326 will indicate the speed of the first vehicle over aperiod of time. If the one or more sensor metrics indicate that thefirst vehicle's speed is below the speed limit by some threshold amountor proportion thereof (e.g., 20 mph in a 55 mph zone, 50% of the postedspeed limit, etc.) and this is maintained for a threshold duration oftime (e.g., 30 seconds, one minute, two minutes, etc.) then controller340 may, upon execution of anomalous condition detection routine 358,conclude that an anomalous condition has been detected. This anomalouscondition may also be correlated to the geographic location associatedwith the geographic location data due to synchronization between thegeographic location data and the sampled telematics data.

Further continuing this example, upon determination of the anomalouscondition, alert notification application 346 may broadcast anotification indicating the detected anomalous condition, the telematicsdata, and/or the geographic location data associated with the detectedanomalous condition. In one aspect, a second vehicle equipped with asecond computing device 300 may receive this data and further determinewhether the anomalous condition is relevant based upon the geographicrelationship between the first and second devices, which is furtherdiscussed below. If the anomalous condition is relevant, then the secondcomputing device 300 may generate an alert indicating the anomalouscondition.

To provide another example by modifying the details of the previous one,aspects may include computing device 300 broadcasting telematics dataand/or geographic location data but not notification data. In accordancewith such aspects, upon being received by a second computing device 300(e.g., a mobile computing device in a second vehicle, an externalcomputing device, a smart infrastructure component, etc.) the secondcomputing device 300 may, determine the relevance of the anomalouscondition based upon the geographic relationship between itself and thefirst computing device 300.

If the second computing device 300 determines that an anomalouscondition, even if present, would be irrelevant or inapplicable basedupon the distance between these devices, the second computing device 300may ignore the telematics data, thereby saving processing power andbattery life. However, if the second computing device 300 determinesthat the geographic location data indicates a potentially relevantanomalous condition, the second computing device 300 may further processthe telematics data and take the appropriate relevant action if ananomalous condition is found (e.g., issue an alert notification,generate an alert, display a warning message, etc.).

To provide yet another example by further modifying the details in theprevious two and including aspects of the examples relating to a trainpassing through a railroad crossing, aspects may include first computingdevice 300 associated with a vehicle or train broadcasting thetelematics data and geographic location data to an external computingdevice (e.g., to external computing device 206 via network 201, as shownin FIG. 2). In addition, the second computing device 300 associated withthe second vehicle (or a first vehicle, in some instances where firstcomputing device 300 is associated with a train) may likewise broadcasttelematics data and geographic location data to the external computingdevice. In accordance with such aspects, the external computing devicemay determine whether an anomalous condition exists and is relevant toone or more of the first and/or second computing devices 300 based upon,for example, a geographic relationship between the first and secondcomputing devices 300. When relevant, external computing device may beconfigured to send alert notifications to the first and/or secondcomputing devices 300, which may include any suitable type ofcommunications such as push notifications, a short messaging service(SMS) message, an email, a notification that used in conjunction withthe OS running on each respective computing device 300, etc. Uponreceiving the notification from the external computing device, the firstand/or second computing device 300 may generate an alert indicating, forexample, a description of the anomalous condition and/or its location.

The geographic relationship between two or more computing devices 300may be utilized in several ways to determine the relevance of theanomalous condition. For instance, current speed, location, route,destination, and/or direction of travel of a first vehicle or a train(collecting and/or associated with the telematics data) may beindividually or collectively compared with current speed, location,route, destination, and/or direction of travel of a first vehicle or asecond vehicle traveling on the road. As one example of the geographicrelationship and use of the train telematics data, a train location,current speed, and/or route, etc. may be compared with a first vehiclelocation, current route, and/or destination, etc. to determine whetherthe first vehicle should divert course or slow down to alleviate therisk of the train and the first vehicle being involved in a collision.

As another example of the geographic relationship, a radius from onevehicle or a train, or a line-of-sight distance between vehicles orbetween a train and a vehicle, may be utilized and compared to athreshold distance. For example, if computing device 300 is implementedas an external computing device and determines a line-of-sight distancebetween a first and second vehicle (or between a vehicle and a train) tobe less than a threshold distance (e.g., a half mile, one mile, etc.),then the external computing device may issue an alert notification toboth vehicles (or to the vehicle and train). In this way, an externalcomputing device may act as an alert management device, processing dataand sending notifications to those devices for which a detectedanomalous condition is relevant.

In another example of the geographic relationship, the geographiclocation data may be correlated with a map database to associate theanomalous condition with a road and to determine the relevance of theanomalous condition based upon other vehicles sharing the road. The mapdatabase may be stored, for example, in a suitable portion of computingdevice 300 (e.g., data storage 360) or retrieved via communications withone or more external computing devices. To provide an illustrativeexample, a computing device 300 may be implemented as an externalcomputing device. The external computing device may determine, fromtelematics data and geographic location data received from a firstcomputing device 300, that a first vehicle is located on a highway at acertain geographic location. If the external computing device determinesthat a second computing device 300 in a vehicle travelling on the samehighway is within a threshold distance approaching the first vehicle,then the external computing device may issue an alert notification tothe second vehicle.

In yet other aspects, the geographic location data may be correlatedwith a geofence database to determine the relevance of the anomalouscondition based upon whether other vehicles are located inside thegeofence. The geofence database may be stored, for example, in asuitable portion of computing device 300 (e.g., data storage 360) orretrieved via communications with one or more external computingdevices. To provide another illustrative example, a computing device 300may be implemented as an external computing device. The externalcomputing device may determine, from telematics data and geographiclocation data received from a first computing device 300, that a firstvehicle is located on a highway at a certain geographic location. Theexternal computing device may calculate a geofence having a shapesubstantially matching the road upon which the first vehicle istravelling.

The geofence may be calculated as having any suitable shape such thatthe appropriate vehicles are notified of the detected anomalouscondition. For example, the geofence shape may follow the contours ofthe road and extend ahead of the first vehicle and behind the firstvehicle some threshold distances, which may be the same or differentthan one another. To provide another example, the geofence shape mayinclude other arterial roads that feed into the road upon which thefirst vehicle is travelling, roads anticipated to be impacted by theanomalous condition, railroad crossings impacted and/or anticipated tobe impacted by the anomalous condition, etc.

In some aspects, the geofence may be adjusted or modified based upon achange in the location of computing device 300. This change may betriggered using any suitable data indicative of potentially increasingroad densities, such as changes in population density data associatedwith the geographic location of the computing device 300, changes in atype of road upon which computing device 300 is determined to betravelling, etc.

For example, a first computing device 300 may be implemented as a mobilecomputing device and associated with a first vehicle, while a secondcomputing device 300 may be implemented as an external computing device.The external computing device may calculate an initial geofence as athreshold distance radius centered about the first vehicle's location.The geographic location data corresponding to the first vehicle'slocation may have associated population density data that is correlatedwith locally stored data or data retrieved by the external computingdevice. When the population density data surpasses a threshold densityvalue, the shape of the geofence may be adjusted from the radiuscentered about the first vehicle's location to include only the roadupon which the first vehicle is travelling. In this way, computingdevice 300 may prevent false alert notifications from being sent toother vehicles travelling in close proximity to the first vehicle, buton nearby roads unaffected by the detected anomalous condition.

To provide another illustrative example, as previously discussed, one ormore cameras integrated as part of sensor array 326 may store imageand/or video data from a vantage point within a vehicle in whichcomputing device 300 is mounted to act as a dashboard camera. Inaccordance with such aspects, anomalous condition detection routine 358may include instructions, that when executed by controller 340,facilitate the analysis of the image and/or video data to detect one ormore anomalous conditions that may pose an immediate threat to thedriver. These anomalous objects may also be identified as a travel ortraffic event, as previously discussed. This analysis may be performedin accordance with any suitable object recognition and/or image analysisto detect images in the path of the vehicle, such as animals,pedestrians, other vehicles, trains, potholes, etc.

Upon detecting an anomalous object, computing device 300 may issue theappropriate alert via display 316 and/or sound an alarm viaspeaker/microphone 322. Additionally or alternatively, computing device300 may, upon detecting an anomaly, broadcast one or more signals viacommunication unit 330, which are received directly or indirectly byother computing devices. Again, these other computing devices may thengenerate alert notifications locally when close to the geographiclocation of computing device 300 where the signal was broadcasted.Aspects in which the detected anomalous condition is shared in thismanner may be particularly useful when the identified anomaly is likelyto threaten other drivers using the same road, such as potholes orobjects blocking the roadway, trains, etc.

Although FIG. 3 depicts controller 340 as including one program memory302, one MP 306, and one RAM 308, controller 340 may include anysuitable number of each of program memory 302, MP 306, and RAM 308.Furthermore, although FIG. 3 depicts controller 340 as having a single110 interface 310, controller 340 may include any suitable number and/ortypes of I/O interfaces 310. In various aspects, controller 340 mayimplement RAM(s) 308 and program memories 302 as any suitable type ofmemory, such as non-transitory computer readable memories, semiconductormemories, magnetically readable memories, and/or optically readablememories, for example.

Exemplary Screenshots of an Alert Notification Application

FIG. 4A illustrates an example mobile computing device home screen 400in accordance with an exemplary aspect of the present disclosure. Invarious aspects, home screen 400 is displayed on a mobile computingdevice, such as mobile computing device 110 or mobile computing devices204.1, 204.2, and/or 212 as shown in FIGS. 1 and 2, respectively. Inaccordance with such aspects, home screen 400 may be displayed as partof a device display, such as display 316, for example, as shown in FIG.3.

Home screen 400 may be displayed as a default screen on a mobilecomputing device. In one embodiment, home screen 400 may facilitate alock screen of a mobile computing device. Lock screens may be typicallydisplayed when a user locks the mobile computing device to enter a lockscreen mode (e.g., by pressing a physical button). Additionally oralternatively, the mobile computing device may revert to the lock screenwhen inactive for a threshold period of time. The lock screen prevents auser from using a portion of the mobile computing device functionality.For example, a lock screen might prevent a mobile computing device in auser's pocket from accidentally sending SMS messages or phone calls.

Although lock screens typically limit the functionality of the devicewhen enabled, it may be desirable for certain applications to provide auser with some functionality via the lock screen. For example, if themobile computing device is used to play music, a lock screen overlaycould allow a user to change tracks, pause a track, or adjust the volumelevel without unlocking the phone. In accordance with some aspects,alert notification 402 may be displayed as part of a home screen and/orlock screen of a mobile computing device, as shown in FIG. 4A.

Although alert notification 402 may be displayed as part of home screen400, other aspects include alert notification 402 being displayed aspart of a notification system separate from home screen 400. Forexample, some mobile phone operating systems (e.g., the Android OS)implement a universal “pull-down” notification system where all incomingnotifications are displayed. In these notification systems, newnotifications are initially previewed in a notification bar at the topof the phone display, and a user may pull down the notification bar(e.g., by using a swiping gesture) to access the details of any receivednotifications. In one aspect, alert notification 402 may be displayed aspart of a notification bar type notification.

As previously discussed with reference to FIG. 3, a device running thealert notification application may be configured to determine whether ananomalous condition has been detected and/or to receive alertnotifications sent by other devices that have done so. In accordancewith such aspects, alert notification 402 is a block diagramrepresentation of what may be generated upon detection of an anomalouscondition and/or receiving an indication that an anomalous condition hasbeen detected. Alert notification 402 may be implemented as any suitablegraphic, label, text, description, etc., to convey this to a user. Inone embodiment, alert notification 402 may be interactive and mayfacilitate a user selection via an appropriate gesture (e.g., swiping,tapping, etc.).

FIG. 4B illustrates an example mobile computing device applicationscreen 450 in accordance with an exemplary aspect of the presentdisclosure. In various aspects, application screen 450 may be displayedon a mobile computing device, such as mobile computing device 110 ormobile computing devices 204.1, 204.2, and/or 212, as shown in FIGS. 1and 2, respectively. In accordance with such aspects, application screen450 may be displayed as part of a device display, such as display 316,for example, as shown in FIG. 3.

In one aspect, application screen 450 may be displayed upon a userselecting alert notification 402 from home screen 400. Applicationscreen 450 may include an alert description 452, an alert location 454,and an alert response 456. Alert description 452 is a block diagramrepresentation of one or more descriptions of the alerts related to thedetected anomalous condition. Alert description 452 may be implementedas any suitable graphic, label, text, description, etc., to convey thisto a user. For example, alert description 452 may include a textdescription such as “slow traffic ahead,” “traffic at standstill ahead,”“unpaved road ahead,” “potential icy conditions ahead,” “pulled overvehicle ahead,” “train passing through railroad crossing ahead,” etc.

Alert location 454 is a block diagram representation of one or moredescriptions of the location of the anomalous condition. Alert location454 may be implemented as any suitable graphic, label, text,description, etc., to convey this to a user. For example, alert location454 may include a directional compass indicating a direction towards theanomalous condition from the mobile computing device displayingapplication screen 450. To provide additional examples, alert location454 may include a distance to the anomalous condition, a map overlaidwith the location of the mobile computing device displaying applicationscreen 450 to indicate the position of the mobile computing device inrelation to the anomalous condition, the threshold distances and/orgeofences used to determine the relevance of the anomalous condition,etc.

Alert response 456 is a block diagram representation of one or moredescriptions of a directed response to the anomalous condition. Alertresponse 456 may be implemented as any suitable graphic, label, text,description, etc., to convey this to a user. For example, alert response456 may include a text indication to “stop at railroad crossing ahead,”a map or other indication of an alternate route for a vehicle to take toavoid waiting at a railroad crossing for a train to pass, etc.

Insurance Applications

As noted herein, the present embodiments may be used to adjust, update,and/or generate insurance policies. Insurance policies, such as auto,usage-based, home, and/or household insurance policies, may be adjusted,updated, and/or generated for insureds or potential customers that havemobile devices and/or vehicles that are equipped or configured with oneor more of the functionalities discussed herein.

For instance, insureds or family members may have mobile devices and/orvehicles that are configured to receive telematics data associated withtrains, other vehicles and/or abnormal road or travel conditions thatother drivers are experiencing. The telematics may be received directlyfrom a train(s) or other vehicles, or indirectly from smartinfrastructure and/or insurance provider remote servers. As a result,the insureds and/or their family members may be timely notified oftraffic or travel events and then may take alternate routes (or even notdrive or delay driving) to lower their risk of getting in an accidentdue to the traffic or travel events. An insurance provider may promoteor reward such risk-averse behavior and/or safer driving with lowerinsurance premiums, rates, and/or increased discounts, such as forusage-based or other types of auto insurance.

Furthermore, an insurance provider may promote or reward the use of oneor more aspects described herein with lower insurance premiums, rates,and/or increased discounts. For example, an insurer may providediscounts or other incentives upon an insured customer installing anapplication to their mobile computing device that enables the mobilecomputing device to broadcast telematics data and/or to generate alertnotifications based upon telematics data received from other devices.

Additionally or alternatively, an insurer may provide discounts or otherincentives upon an amount that an insured customer uses the telematicsapplication on their mobile computing device that enables the mobilecomputing device to broadcast telematics data and/or to generate alertnotifications based upon telematics data received from other devices.Such usage-based discounts or incentives may be based upon amount oftime of, or number of miles of, use or usage, e.g., an amount of time ormiles that the insured drove during a specific period with a TelematicsApp running or executing on their mobile device (which was locatedwithin the insured vehicle as it travels), the Telematics App configuredto collect and broadcast telematics data, and/or to receive telematicsdata from other vehicles or devices, and generate alerts orrecommendations based upon the data received.

Exemplary Smart Control Systems

FIG. 5 illustrates a block diagram of an exemplary smart vehicle controlsystem 500 in accordance with an exemplary aspect of the presentdisclosure. In one aspect, smart vehicle control system 500 may beimplemented as any suitable computing device, such as a computing devicethat is integrated as part of a smart vehicle to facilitate autonomousdriving and/or other smart driving functions. For example, smart vehiclecontrol system may be integrated as part of one or more vehicles202.1-202.N, as shown in FIG. 2, to provide such vehicles with suchfunctions. Smart driving functions may include, for example, thegeneration, receipt, collection, storage, and/or transmission oftelematics data and/or other suitable data, such as previously discussedabove with reference to on board computer 114, as shown in FIG. 1. Othersuitable data may include other data discussed herein, such as, forexample, geographic location data as discussed herein. In an aspect, asmart train controller or smart train control system may include similarfeatures as smart vehicle control system 500 and may additionally oralternatively be integrated as part of a train (e.g., train 210), asfurther described below.

Smart vehicle control system 500 may include a sensor array 526, acommunication unit 530, a smart vehicle controller 540, one or morevehicle sensors 545, and/or a driving control system 550, one or more ofwhich may be configured to communicate with one another to receive datafrom, and send data to, one another. Smart vehicle control system 500may include additional, less, or alternate functionality, including thatdiscussed elsewhere herein, and/or discussed with reference to computingdevices (e.g., mobile computing devices), remote servers, externalcomputing devices, smart infrastructure, and/or trains.

In an aspect, sensor array 526, communication unit 530, and smartvehicle controller 540 may have a similar architecture, implementation,and/or perform similar functions as sensor array 326, communication unit330, and controller 340, respectively, as previously discussed abovewith reference to FIG. 3. Therefore, only differences between sensorarray 526, communication unit 530, and smart vehicle controller 540, asshown in FIG. 5, and sensor array 326, communication unit 330, andcontroller 340, as shown in FIG. 3, will be further discussed herein.

For instance, it will be appreciated that some differences betweensensor array 526, communication unit 530, and smart vehicle controller540, as shown in FIG. 5, and sensor array 326, communication unit 330,and controller 340, as shown in FIG. 3, respectively, may be due todifferences between applications and design requirements of computingdevices and vehicles. For example, smart vehicle controller 540 mayinclude one or more microprocessors, program memory, RAM, I/Ointerfaces, etc. However, smart vehicle controller 540 may includefaster microprocessors, additional memory, faster memory controllers,etc., than that of controller 340 to account for the additionalprocessing and speed requirements associated with the higher processingfunctions of vehicles, particularly smart vehicles. To provide anotherexample, smart vehicle controller 540 may include one or more processorsspecifically designed for adaptive vision processing at high speedsand/or utilizing parallel processing techniques to facilitate autonomousor semi-autonomous driving.

Likewise, sensor array 526 may have additional or alternative sensors,meters, and/or other suitable devices as compared to sensor array 326.Sensor array 526 may additionally or alternatively include any suitablenumber and/or type of sensors, meters, and/or other suitable devices tofacilitate autonomous or semi-autonomous driving. Examples of sensorsincluded in sensor array 526 may include, for example, radar systemsconfigured to operate at any suitable number or range of wavelengths(e.g., millimeter-wavelengths), Lidar, ultrasonic sensors, etc.

Vehicle sensors 545 may include, for example, any suitable number and/ortype of sensors, meters, and/or other suitable devices integrated aspart of the vehicle in which smart vehicle control system 500 isinstalled or otherwise implemented. For example, vehicle sensors 545 maygenerate one or more sensor metrics or other data that is part of thetelematics data and/or other data that is stored, collected, and/orbroadcasted from smart vehicle control system 500 (e.g., viacommunication unit 530).

In some aspects, vehicle sensors 545 may sample sensor metrics or otherinformation that is included as part of the telematics data and/or otherdata, as discussed elsewhere herein, while sensor array 526 may beimplemented as one or more sensors associated with autonomous drivingfunctions. Thus, in aspects in which smart vehicle control system 500 isimplemented as part of a non-autonomous vehicle, vehicle sensors 545 andsensor array 526 may be implemented as a single sensor array.

Communication unit 530 may be configured to transmit telematics data(and/or other suitable data) including one or more sensor metrics orother information generated by vehicle sensors 545 and/or sensor array526, which may be received by other computing devices (e.g., mobilecomputing devices), other smart vehicles, smart infrastructure, externalcomputing devices, and/or trains, as discussed elsewhere herein.Additionally or alternatively, communication unit 530 may be configuredto receive telematics data (and/or other suitable data) from othercomputing devices (e.g., mobile computing devices), other smartvehicles, smart infrastructure, external computing devices, and/ortrains, as discussed elsewhere herein.

When transmitting telematics data and/or other data discussed herein,smart vehicle controller 540 may be configured to format the sensormetrics and/or other information generated, collected, and/or measuredby vehicle sensors 545 and/or sensor array 526 into a data broadcast,determine whether the telematics data and/or other data should beupdated, and/or broadcast the telematics data and/or other data.Additionally or alternatively, smart vehicle controller 540 may beconfigured to analyze the telematics data and/or other data to identifyone or more anomalous conditions (e.g. travel events, traffic events),and/or alerts, to generate one or more messages associated with thetelematics data (and/or other data) and/or detailing the type and/orextent of an identified anomaly and/or alert, etc.

Furthermore, smart vehicle controller 540 may be configured to broadcastor otherwise direct a transmission of the message via data transmissionand/or wireless communication (e.g., via communication unit 530) toanother computing device (such as a mobile computing device, anothervehicle, a remote server, smart infrastructure, etc.). As furtherdiscussed herein, devices receiving the message and/or the telematicsdata and/or other data may utilize such received information to performvarious functions, issue alerts to drivers, etc. In this way, themessages, telematics data, and/or other data transmitted by smartvehicle control system 500 may facilitate safer travel for anothervehicle and/or another driver.

Similar to the other devices described above (e.g., mobile computingdevice 300) when receiving data, smart vehicle controller 540 may beconfigured to perform various functions such as issuing alerts todrivers when the data contains a warning message and/or identifying ananomalous condition by analyzing the received data.

Driving control system 550 may be implemented with any suitable numberand/or type of driving controllers to control the direction, movement,and/or speed of the vehicle in which smart vehicle control system 500 isinstalled. For example, driving control system 550 may include variousdrive-by-wire interfaces to facilitate controlling the speed of thevehicle and to turn the vehicle without user input. To provide anadditional example, driving control system may include various brakingcontrollers and/or transmission controllers to slow the vehicle and toshift the vehicle into different gears.

In accordance with one aspect, smart vehicle controller 540 maycommunicate with one or more components of driving control system 550 inresponse to telematics data, information, and/or messages received viacommunication unit 530. For example, if the telematics data indicates aroad hazard at a certain location and/or in a certain road lane, thensmart vehicle controller 540 may issue one or more commands to drivingcontrol system 550 to steer the vehicle into a clear lane, thus avoidingthe road hazard. As another example, if the telematics data and/or oneor more messages indicate that a train is within a predetermineddistance of a railroad crossing, then smart vehicle controller 540 mayissue one or more commands to driving control system 550 to re-route orstop the vehicle.

Driving control system 550 may include different types of feedbackcomponents and/or control systems based upon the type of vehicle inwhich smart vehicle control system 500 is implemented or installed. Forexample, driving control system 550 may include various interfacesand/or control systems to facilitate autonomous driving in conjunctionwith smart vehicle controller 540. But if smart vehicle control system500 is implemented in a non-autonomous vehicle, driving control system550 may work in conjunction with smart vehicle controller 540 to receiveone or more signals and/or data associated with traditional drivingfunctions (e.g., manual acceleration, steering, braking, etc.).

Regardless of the type of vehicle in which smart vehicle control system500 is implemented, smart vehicle controller 540 may work in conjunctionwith driving control system 550 to support any suitable number and/ortypes of driver feedback. To provide this feedback, driving controlsystem 550 may include any suitable number and/or types of displays,user interfaces, speakers, buzzers, etc.

For example, driving control system 550 may include various feedbackcomponents to provide visual and/or auditory feedback regarding theoperation of the vehicle and/or information regarding anomalousconditions, alerts, warnings, recommendations, etc., which may be basedupon an analysis of telematics data and/or other suitable data. Again,the telematics data and/or other suitable data may be received fromanother computing device (e.g., via communication unit 530) and/orgenerated and analyzed locally at smart vehicle control system 500.

To provide another example, smart vehicle controller 540 may include oneor more memory units configured to store cartographic and/or map data.In response to user input received via a user interface implemented bydriving control system 550, smart vehicle controller 540 may generate,calculate, and/or display travel routes, which may provide navigationalguidance to a driver. Furthermore, smart vehicle controller 540 mayperform functions associated with the determination of whether anidentified anomaly (e.g., a traffic event, travel event such as anapproaching train, abnormal condition, etc.), which has been determinedfrom an analysis of received telematics data from another device, isrelevant to the vehicle in which smart vehicle control system 500 isimplemented.

This determination of relevance may be made, for example, by comparing alocation (e.g., geographic coordinates included in a telematics datatransmission) to the current location of the vehicle in which smartvehicle control system 500 is implemented to determine whether thelocations are within a threshold distance of one another. Thedetermination may also be made, for example, when the identified anomalyor other abnormal condition is or will be (e.g., in the case of anapproaching train) located along a current travel route (e.g., ahead bysome threshold distance in a direction of travel on the same road onwhich the vehicle is moving). If so, aspects include smart vehiclecontroller 540 automatically performing various preventative and/orcorrective actions based upon how the relevance of the identifiedanomaly is determined. For example, smart vehicle controller 540 mayissue a visual and/or audible alert via driving control system 550,calculate and display a new travel route via driving control system 550that avoids the location of the identified event, etc.

In some aspects, the preventative and/or corrective actions may beissued only when it is determined that an identified anomaly isrelevant, and is otherwise not issued. For example, aspects include anidentified anomaly that is not along a current route for the vehicle inwhich smart vehicle control system 500 is implemented not causing analarm to be sounded and/or the route to be adjusted, even if thelocation of the anomaly is otherwise nearby. In this way, the preventiveor corrective action may alleviate or avoid a negative impact of theabnormal travel condition on the driver and/or the vehicle in whichsmart vehicle control system 500 is implemented to facilitate safer ormore efficient vehicle travel. Additional details of the preventive orcorrective action that may be facilitated by smart vehicle controlsystem 500 (or another suitable computing device or system) are furtherdiscussed below with reference to FIGS. 6-8.

As noted above, in an aspect, a smart train controller or smart traincontrol system may include similar features as smart vehicle controlsystem 500 and may be integrated as part of a train (e.g., train 210).Thus, for instance, a smart train control system may include a smarttrain controller, train sensors, a communication unit, a sensor array,and/or a train operation control system configured to perform functionssimilar to those discussed with reference to smart vehicle controlsystem 500, but in the context of a train (e.g., train 210) and traintelematics data and/or other suitable data as discussed herein.

Exemplary Railroad Crossing Embodiments

FIG. 6 illustrates an exemplary method 600 of using train telematicsdata to reduce risk of accidents. In the present aspect, the method 600may be implemented by any suitable computing device (e.g., mobilecomputing devices 204.1 and/or 204.2, mobile computing device 212,external computing device 206, vehicles 202.1 and/or 202.2, train 210,and/or infrastructure component 208, as shown in FIG. 2). In one aspect,the method 600 may be performed by one or more processors, applications,and/or routines, such as any suitable portion of controller 340,software applications 344, and/or software routines 352, for example, asshown in FIG. 3.

The method 600 may include receiving train telematics data associatedwith a train (block 602). The train telematics data may be received viaat least one of one or more autonomous vehicle processors (e.g., one ormore processors of the mobile computing device 204.1 where the vehicle202.1 is an autonomous vehicle, one or more processors of a smartvehicle controller where the vehicle 202.1 is an autonomous vehicle,etc.) or associated transceivers (e.g., one or more transceivers of themobile computing device 204.1, one or more transceivers of a smartvehicle controller of the vehicle 202.1, etc.) (block 602). The traintelematics data may be received via wireless communication or datatransmission directly from a train transceiver (e.g., of train 210) orindirectly from a railroad crossing (e.g., a smart railroad crossingthat may be an implementation of infrastructure component 208) (block602). The train telematics data may include at least one of GPS locationdata, speed data, route data, heading data, acceleration data, or trackdata associated with train 210 (block 602).

In one aspect, the train telematics data may be received by receiving abroadcast via a mobile device Telematics App (e.g., alert notificationapplication 346), which may listen for a telematics or other broadcast(block 602). When a telematics broadcast is detected, the traintelematics data may be received by, for example, mobile computing device204.1 and downloaded or otherwise stored in a memory (block 602). Thismay include the mobile computing device 204.1 receiving the traintelematics data from one or more of, for example, mobile computingdevice 204.2, a dedicated train device such as that discussed herein,and/or infrastructure component 208 (which, again, may be implemented asa smart railroad crossing) (block 602).

In another aspect, the received train telematics data may additionallyor alternatively include at least one of a timestamp, one or more sensormetrics indicative of braking motion of train 210, one or more sensormetrics indicative of acceleration motion of train 210, one or moresensor metrics indicative of cornering motion of train 210, or one ormore sensor metrics indicative of a direction of train 210 (block 602).

In yet another aspect, the received train telematics data mayadditionally or alternatively include at least one of the speed dataassociated with train 210, the acceleration data associated with train210, deceleration data associated with train 210, the GPS locationassociated with train 210, or lane information associated with train 210(block 602). The lane information associated with train 210 may, in someaspects, be indicative of a lane that an autonomous vehicle (e.g.,vehicle 202.1) is traveling in so as to facilitate a determination ofwhether the autonomous vehicle can safely drive through a railroadcrossing when the train 210 is passing through, will be passing through,etc., the railroad crossing, as further discussed below (block 602).

In still another aspect, the received train telematics data mayadditionally or alternatively include at least one of time dataassociated with train 210, braking data associated with train 210, leftand/or right turn data associated with train 210, heading dataassociated with train 210, GPS speed data associated with train 210, GPSlatitude and longitude data associated with train 210, gyroscope dataassociated with train 210, battery level data associated with train 210,or telephone usage data associated with train 210 (block 602).

As noted above, in various aspects, examples of the received traintelematics data as described herein may be data of train 210 itselfand/or data of an autonomous vehicle (e.g., vehicle 202.1) (block 602).For instance, the aforementioned braking data, left and/or right turndata, heading data, GPS speed data, GPS latitude and longitude data,gyroscope data, battery level data, and telephone usage data, amongother examples, may be data of train 210 itself and/or data of anautonomous vehicle (block 602). It should be appreciated that when suchdata is data of an autonomous vehicle, such data may be regarded asbeing associated with train 210 because of the relevance of such data indetermining, for example, whether the autonomous vehicle can safelydrive through a railroad crossing, as further discussed below (block602).

The method 600 may include determining (e.g., via the one or moreautonomous vehicle processors) (1) when, or a time period of when, train210 will pass through or be passing through a railroad crossing, or (2)when train 210 is within a predetermined distance of the railroadcrossing (block 604). This determination may be based upon the traintelematics data, and the railroad crossing referred to in thedetermination may be the same railroad crossing from which the traintelematics data may be indirectly received (block 604). Alternatively,the railroad crossing may be another railroad crossing, such as arailroad crossing adjacent to the railroad crossing from which the traintelematics data may be indirectly received (e.g., the other railroadcrossing may be a next railroad crossing along a route traveled by train210) (block 604).

In one aspect, the determination described with respect to block 604 maybe based upon at least one of the GPS location data associated withtrain 210, the speed data associated with train 210, the heading dataassociated with train 210, the route data associated with train 210, orthe track data associated with train 210 (block 604). Additionally oralternatively, the determination described with respect to block 604 maybe based upon comparison via the one or more autonomous vehicleprocessors of (i) at least one of the GPS location data associated withtrain 210, the speed data associated with train 210, the heading dataassociated with train 210, the route data associated with train 210, orthe track data associated with train 210 with (ii) a GPS location of therailroad crossing or the other railroad crossing and a current time(block 604).

In one aspect, train 210 may have a dedicated device installed orotherwise mounted in train 210, which may include a transceiver, acontroller, a GPS unit, a navigation map database, etc. (block 604). Bycomparing the train's current geographic location to railroad crossinglocations stored in a navigation map database, the controller maydetermine that train 210 is approaching, or within a given thresholddistance, of the railroad crossing (block 604). In such a case, thededicated device may generate and broadcast train telematics data, aspreviously discussed above with reference to the mobile computingdevices 204.1-204.N of FIG. 2, so that the determination described withrespect to block 604 may be performed (block 604).

To provide another example, aspects include alert notificationapplication 346 facilitating a mobile computing device located on train210 (e.g., mobile computing device 212, which may be carried by trainpersonnel) determining when train 210 is within a threshold distance ofthe railroad crossing, and generating and broadcasting the traintelematics data upon this condition being satisfied so that thedetermination described with respect to block 604 may be performed(block 604).

Additionally or alternatively, a smart railroad crossing may detect thattrain 210 is approaching, such as via wireless communication with thededicated device and/or via wireless communication with the mobilecomputing device located on train 210. As discussed above with referenceto FIG. 2, the smart railroad crossing may include, for instance, anysuitable combination of components to facilitate this functionality. Forexample, the smart railroad crossing may include a processor, atransceiver, a memory, and/or other suitable components. The smartrailroad crossing may broadcast a signal indicating the arrival of train210 at the crossing (e.g., once train 210 is within a predetermined orthreshold distance of the railroad crossing) to vehicles or mobiledevices approaching, or within proximity of, the railroad crossing sothat the determination described with respect to block 604 may beperformed (block 604).

Thus, in various aspects, the method 600 may include broadcasting traintelematics, route, and/or destination data, for example, which may bereceived by one or more other mobile computing devices in the vicinityof the railroad crossing so that the determination described withrespect to block 604 may be performed (block 604).

The method 600 may include determining (e.g., via the one or moreautonomous vehicle processors) whether the autonomous vehicle can safelydrive through the railroad crossing (block 606). For instance, thisdetermination may be or include a determination of whether theautonomous vehicle can safely drive through the railroad crossing beforea crossing signal is sounded, and/or whether the autonomous vehicle cansafely drive through the railroad crossing without a collision withtrain 210 or without train 210 coming within a threshold distance of therailroad crossing, etc. (block 606). The determination described withrespect to block 606 may be performed by way of the anomalous conditiondetection routine 358 based upon any suitable data and/or other factors,such as based upon a suitable comparison of the train telematics data ora portion thereof with, for example, geographic location data and/orother telematics data of the autonomous vehicle (e.g., vehicle 202.1)(block 606). The geographic location data and/or other telematics dataof the autonomous vehicle may be determined as discussed above, such asby executing instructions of telematics collection routine 354 and/orgeographic location determination routine 356 (block 606). For instance,the mobile device Telematics App may compare the train telematics datawith a speed of the autonomous vehicle, and/or with the autonomousvehicle's route, location, etc. (block 606).

If it is determined that the autonomous vehicle can safely drive throughthe railroad crossing, method 600 may revert to the receipt of traintelematics data associated with train 210 (block 602). If it isdetermined that the autonomous vehicle cannot safely drive through therailroad crossing, method 600 may continue (block 608).

The method 600 may include determining an alternate route for theautonomous vehicle to take to avoid waiting at the railroad crossing(which, as noted above, may be the same railroad crossing from which thetrain telematics data may be indirectly received or may be anotherrailroad crossing) (block 608). In this manner, train 210 may be allowedto pass through the railroad crossing (block 608). This determinationmay be made via the one or more autonomous vehicle processors based upontelematics data and/or geographic location data of the autonomousvehicle and/or train 210, which may be collected, broadcast, etc. asdescribed above (block 608). This determination may also oralternatively be made using other data, such as map data stored by, forexample, mobile computing device 204.1 (block 608). For instance, theone or more autonomous vehicle processors may use telematics data and/orgeographic location data of the autonomous vehicle and/or train 210, andmap data, to determine an alternate route that follows known roadstoward a destination of the autonomous vehicle and that will, based uponthe telematics data and/or geographic location data, avoid atrain-vehicle collision (block 608).

The method 600 may include directing (e.g., via the one or moreautonomous vehicle processors) the autonomous vehicle to (1)automatically travel along the alternate route, or (2) automaticallystop at the railroad crossing to allow train 210 to pass (block 610).For instance, if the one or more autonomous vehicle processors areunable to determine a suitable alternate route using the telematics dataand/or geographic location data, and map data, as described above withrespect to block 608 (e.g., if the acts described with respect to block608 are unable to be performed), then the autonomous vehicle may bedirected to automatically stop at the railroad crossing (block 610). Theone or more autonomous vehicle processors may be unable to determine asuitable alternate route if, for instance, an alternate route isdetermined but would take the autonomous vehicle more time to travelalong than the autonomous vehicle would need to wait at the railroadcrossing for the train to pass (block 610). In another instance, the oneor more autonomous vehicle processors may be unable to determine asuitable alternate route if the alternate route includes one or moreroads that are more than a threshold distance from the original route,etc. (block 610).

When the autonomous vehicle is directed to automatically travel alongthe alternate route, the alternate route may be displayed on a displayof a mobile computing device of the autonomous vehicle (e.g., display316 of mobile computing device 204.1) (block 610). In any event, itshould be appreciated that performance of one or more of the actsdescribed herein may allow train 210 to pass unimpeded and mayfacilitate avoidance of train-vehicle collisions and safer train andvehicle travel (block 610).

The method 600 may include broadcasting (e.g., via the one or moreautonomous vehicle processors and/or the one or more associatedtransceivers) a message to other autonomous vehicles that (1) directsthe other autonomous vehicles to travel along at least one alternateroute, and/or (2) directs the other autonomous vehicles to automaticallystop at the railroad crossing (block 612). For each autonomous vehicle,the message may be either to travel along an alternate route thatcompletely avoids the railroad crossing or to automatically stop at therailroad crossing; that is, one or more autonomous vehicles may receivea message to travel along an alternate route(s) and one or moreautonomous vehicles may receive a message to automatically stop at therailroad crossing (block 612). Moreover, for each autonomous vehicle,and as discussed above, a message to automatically stop at the railroadcrossing may be a message to automatically stop at the same railroadcrossing from which the train telematics data may be indirectly receivedor another railroad crossing (block 612). In one aspect, a message toautomatically stop at the railroad crossing may be a message toautomatically stop at the railroad crossing during a predetermined timeperiod to allow train 210 to pass unimpeded to facilitate avoidance oftrain-vehicle collisions (block 612).

The method 600 may include at least one of displaying, adjusting, orgenerating an insurance discount for vehicles (e.g., autonomousvehicles) having risk mitigation or prevention functionality such asthat described herein (e.g., functionality associated with receiving awireless communication broadcast including the train telematics data,analyzing the train telematics data, and directing corrective actionsbased upon the train telematics data as described with respect to themethod 600) (block 614). The at least one of the displaying, adjusting,or generating an insurance discount may be performed via, for example,the one or more autonomous vehicle processors and/or an insuranceprovider remote server (block 614). Moreover, such acts may be performedand results may be displayed or otherwise communicated via, for example,an insurance provider remote server and/or a mobile computing device, asalso described hereinabove (block 614). In some aspects, the insurancediscount may be time or mileage usage-based based upon an amount ofusage of the risk mitigation or prevention functionality, as alsodescribed hereinabove (block 614). Moreover, in some aspects, aninsurance provider remote server (implementations of which are discussedabove) may adjust an insurance premium or discount by receivingtelematics data from an insured mobile device, which telematics data mayinclude an indication of a level of usage of the alert, recommendation,and/or other functionality discussed herein (block 614).

The method 600 may include additional, less, or alternate actions,including those discussed elsewhere herein, and/or may be implementedvia one or more local or remote processors (e.g., mobile device, train,EMS vehicle, destination vehicle, and/or remote server processors), orvia computer-executable instructions stored on non-transitorycomputer-readable medium or media.

FIG. 7 illustrates an exemplary method 700 of using train telematicsdata to reduce risk of accidents via a mobile device traveling within avehicle. In the present aspect, the method 700 may be implemented by anysuitable computing device (e.g., mobile computing devices 204.1 and/or204.2, mobile computing device 212, external computing device 206,vehicles 202.1 and/or 202.2, train 210, and/or infrastructure component208, as shown in FIG. 2). In one aspect, the method 700 may be performedby one or more processors, applications, and/or routines, such as anysuitable portion of controller 340, software applications 344, and/orsoftware routines 352, for example, as shown in FIG. 3.

The method 700 may include receiving train telematics data associatedwith a train (block 702). The train telematics data may be received viawireless communication or data transmission (block 702). Moreover, thetrain telematics data may be received via at least one of one or moreprocessors of a mobile device (e.g., mobile computing device 204.1)traveling within a vehicle (e.g., vehicle 202.1) or one or moreassociated transceivers (e.g., one or more transceivers of mobilecomputing device 204.1) (block 702). Aside from the inclusion of suchaspects in which the train telematics data may be received by the atleast one of the one or more processors of the mobile device travelingwithin the vehicle (which may be, but need not be, an autonomousvehicle) or the one or more associated transceivers, the acts describedwith respect to block 702 may be similar to those described with respectto block 602. Thus, the train telematics data may be received directlyfrom a train transceiver (e.g., of train 210) or indirectly from arailroad crossing (e.g., a smart railroad crossing that may be animplementation of infrastructure component 208) (block 702). The traintelematics data may include data such as example types of data describedwith respect to block 602. Moreover, the train telematics data may bereceived by receiving a broadcast via a Telematics App of the mobiledevice, as also described more fully with respect to block 602.

The method 700 may include determining (e.g., via the one or moreprocessors of the mobile device) (1) when, or a time period of when,train 210 will pass through or be passing through a railroad crossing,or (2) when train 210 is within a predetermined distance of the railroadcrossing (block 704). This determination may be based upon the traintelematics data and, aside from being performed by, for example, one ormore processors of the mobile device which need not be in an autonomousvehicle, may be performed in the manner described with respect to block604. Similarly, a dedicated device installed or otherwise mounted intrain 210 may generate and broadcast the train telematics data asdescribed with respect to block 604; alert notification application 346may facilitate such generation and broadcasting as described withrespect to block 604; a smart railroad crossing may broadcast a signalindicating the arrival of train 210 at the railroad crossing asdescribed with respect to block 604; etc. (block 704).

Thus, in various aspects, the method 700 may include broadcasting traintelematics, route, and/or destination data, for example, which may bereceived by one or more other mobile computing devices in the vicinityof the railroad crossing so that the determination described withrespect to block 704 may be performed (block 704).

The method 700 may include determining (e.g., via the one or moreprocessors of the mobile device) whether the vehicle can safely drivethrough the railroad crossing (block 706). For instance, thisdetermination may be or include a determination of whether the vehiclecan safely drive through the railroad crossing before a crossing signalis sounded, and/or whether the vehicle can safely drive through therailroad crossing without a collision with train 210 or without train210 coming within a threshold distance of the railroad crossing, etc.(block 706). The determination described with respect to block 706 maybe performed, for example, in one of the example ways described withrespect to block 606.

If it is determined that the vehicle can safely drive through therailroad crossing, method 700 may revert to the receipt of traintelematics data associated with train 210 (block 702). If it isdetermined that the vehicle cannot safely drive through the railroadcrossing, method 700 may continue (block 708).

The method 700 may include determining an alternate route for thevehicle to take to avoid waiting at the railroad crossing (which, aswith the method 600, may be the same railroad crossing from which thetrain telematics data may be indirectly received or may be anotherrailroad crossing) (block 708). In this manner, train 210 may be allowedto pass through the railroad crossing (block 708). This determinationmay be made, for instance, in one of the example ways described withrespect to block 608.

The method 700 may include causing (e.g., via the one or more processorsof the mobile device) the alternate route to be displayed on a displayof the mobile device (e.g., display 316 of mobile computing device204.1) or a vehicle navigation system (e.g., a vehicle navigation systemof vehicle 202.1) (block 710). It should be appreciated that performanceof one or more of the acts described herein may allow train 210 to passunimpeded and may facilitate avoidance of train-vehicle collisions andsafer train and vehicle travel (block 710).

The method 700 may include at least one of displaying, adjusting, orgenerating an insurance discount for vehicles having risk mitigation orprevention functionality such as that described herein (e.g.,functionality associated with receiving a wireless communicationbroadcast including the train telematics data, analyzing the traintelematics data, and directing corrective actions based upon the traintelematics data as described with respect to the method 700) (block712). The at least one of the displaying, adjusting, or generating aninsurance discount may be performed via, for example, the one or moremobile processors of the mobile device and/or an insurance providerremote server (block 712). In some aspects, the insurance discount maybe time or mileage usage-based based upon an amount of usage of the riskmitigation or prevention functionality, and/or an insurance providerremote server may adjust an insurance premium or discount by receivingtelematics data from an insured mobile device, as described above withrespect to block 614.

The method 700 may include additional, less, or alternate actions,including those discussed elsewhere herein, and/or may be implementedvia one or more local or remote processors (e.g., mobile device, train,EMS vehicle, destination vehicle, and/or remote server processors), orvia computer-executable instructions stored on non-transitorycomputer-readable medium or media.

FIG. 8 illustrates an exemplary method 800 of utilizing train telematicsdata. In the present aspect, the method 800 may be implemented by anysuitable computing device(s) (e.g., mobile computing devices 204.1and/or 204.2, mobile computing device 212, external computing device206, vehicles 202.1 and/or 202.2, train 210, and/or infrastructurecomponent 208, as shown in FIG. 2). In one aspect, the method 800 may beperformed by one or more processors, applications, and/or routines, suchas any suitable portion of controller 340, software applications 344,and/or software routines 352, for example, as shown in FIG. 3.

The method 800 may include receiving, by a smart railroad crossinginfrastructure (e.g., an implementation of infrastructure component208), train telematics data from a mobile computing device located on(or otherwise associated with) a train (e.g., mobile computing device212 located on or otherwise associated with train 210) (block 802).Receipt of train telematics data by a smart railroad crossinginfrastructure is discussed in further detail above with respect to, forexample, FIG. 6.

The method 800 may include broadcasting, by the smart railroad crossinginfrastructure, the train telematics data received from the mobilecomputing device (block 804). Broadcasting of train telematics data by asmart railroad crossing infrastructure is discussed in further detailabove with respect to, for example, FIG. 6.

The method 800 may include receiving, by a first mobile computing devicelocated in a vehicle (e.g., mobile computing device 204.1 located invehicle 202.1), the train telematics data from a second mobile computingdevice located on train 210 (block 806). The second mobile computingdevice may be the mobile computing device described above with respectto blocks 802 and 804 (e.g., mobile computing device 212) (block 806).In some aspects, the acts described with respect to blocks 802 and 804may not be performed, and the method 800 may begin with the actsdescribed with respect to block 806. The train telematics data mayinclude information indicative of at least one of a speed, a heading, ora location of train 210 (block 806).

The method 800 may include determining, by the first mobile computingdevice, at least one of a speed, a location, or a route of the vehicle(block 808). This determination may be made by, for example, aTelematics App of the first mobile computing device, with examplefunctionality of a Telematics App being further discussed above (block808).

The method 800 may include determining, by the first mobile computingdevice, whether the vehicle can safely cross a railroad crossing (whichmay be the smart railroad crossing referred to above with respect toblocks 802 and 804 or a different railroad crossing) (block 810). Forinstance, this determination may be performed by the first mobilecomputing device based upon a comparison between (1) the at least one ofthe speed, the location, or the route of the vehicle, and (2) the atleast one of the speed, the heading, or the location of train 210 asderived from the train telematics data (block 810). In one aspect, thedetermination of whether the vehicle can safely cross the railroadcrossing may be a determination of whether the vehicle will be able tocross the railroad crossing before at least one of (1) a crossing signalassociated with the railroad crossing is sounded (e.g., indicating thatone or more gates associated with railroad crossing are closing or aboutto close), or (2) train 210 is within a threshold distance from therailroad crossing (block 810), Examples of determining train locationrelative to a railroad crossing are further discussed above.

If it is determined that the vehicle can safely cross the railroadcrossing, method 800 may revert to the acts described with respect toblock 802 (or to the acts described with respect to block 806, forexample, in aspects where the acts described with respect to blocks 802and 804, for example, are not performed). If it is determined that thevehicle cannot safely cross the railroad crossing, method 800 maycontinue (block 812).

The method 800 may include issuing (e.g., by the first mobile computingdevice) at least one of an audible alarm or a visual alarm before the atleast one of (1) the crossing signal is sounded or (2) train 210 iswithin the threshold distance from the railroad crossing (block 812).For instance, an audible alarm may be issued via speaker/microphone 322,and/or a visual alarm may be issued via display 316 (block 812).

The method 800 may include adjusting, by the first mobile computingdevice, a currently calculated driving route (block 814). The adjustedroute may be determined, for example, in the manner described above fordetermining an alternate route (e.g., as described with respect to block608) (block 814). The adjusted route may avoid the railroad crossing(block 814).

The method 800 may include at least one of displaying, adjusting, orgenerating an insurance discount for vehicles having risk mitigation orprevention functionality such as that described herein (e.g.,functionality associated with the first mobile computing device asdescribed herein) (block 816). The at least one of the displaying,adjusting, or generating an insurance discount may be performed via, forexample, one or more processors of the first mobile computing deviceand/or an insurance provider remote server (block 816). In some aspects,the insurance discount may be time or mileage usage-based based upon anamount of usage of the risk mitigation or prevention functionality,and/or an insurance provider remote server may adjust an insurancepremium or discount by receiving telematics data from an insured mobiledevice, such as the first mobile computing device, as described abovewith respect to block 614.

The method 800 may include additional, less, or alternate actions,including those discussed elsewhere herein, and/or may be implementedvia one or more local or remote processors (e.g., mobile device, train,EMS vehicle, destination vehicle, and/or remote server processors), orvia computer-executable instructions stored on non-transitorycomputer-readable medium or media.

Train Telematics/Smart Train Controller

In one aspect, a computer-implemented method of using train telematicsdata to reduce risk of collisions may be provided. The method mayinclude (1) generating, via one or more processors (such as a smarttrain controller) or a Telematics App, train telematics data associatedwith movement of a train, the train telematics data including GPSlocation, speed, route, heading, acceleration, and/or track data; (2)determining, via the one or more processors, when the train is within apredetermined distance of a railroad crossing based upon the traintelematics data; and/or (3) when the train is determined to be withinthe predetermined distance of the railroad crossing and moving towardthe railroad crossing, broadcasting via the one or more processors (suchas via wireless communication or data transmission) an alert or thetrain telematics data (i) directly or indirectly to nearby autonomousvehicles to facilitate the autonomous vehicles avoiding or stopping atthe railroad crossing, or (ii) directly or indirectly to smart railroadcrossing infrastructure (e.g., a smart railroad crossing) to allowautomatic gate closing or other visual alerts at the railroad crossingto avoid train-vehicle collisions.

In another aspect, a computer-implemented method of using traintelematics data to reduce risk of collision may be provided. The methodmay include (1) generating, via one or more processors (such as a smarttrain controller) or a Telematics App, telematics data associated withmovement of a train, the train telematics data including GPS location,speed, route, heading, acceleration, and/or track data; (2) determining,via the one or more processors, a time period of when the train will bepassing through a railroad crossing based upon the train telematics data(such as based upon train GPS location, speed, heading, route, and/ortrack information, and/or comparison with a GPS location of the railroadcrossing); and/or (3) when it is determined that the train is within thepredetermined distance of the railroad crossing and moving toward therailroad crossing, broadcasting via the one or more processors (such asvia wireless communication or data transmission): (a) the time period ofwhen the train will be passing through the railroad crossing, (b) analert, and/or (c) the train telematics data (i) directly or indirectlyto autonomous vehicles to facilitate the autonomous vehiclesautomatically avoiding (such as re-routing themselves based upon acurrent destination and the train telematics data) and/or automaticallystopping at the railroad crossing, or (ii) directly or indirectly tosmart railroad crossing infrastructure to allow automatic gate closingor generation of other visual alerts at the smart railroad crossing toavoid train-vehicle collisions.

The foregoing methods may include additional, less, or alternateactions, including those discussed elsewhere herein. For instance, thetelematics data may include data selected from one or more of, and notlimited to all of: a timestamp; one or more sensor metrics indicative ofbraking motion of the train; one or more sensor metrics indicative ofacceleration motion of the train; one or more sensor metrics indicativeof cornering motion of the train; and one or more sensor metricsindicative of a direction of the train. The telematics data may includespeed, acceleration, deceleration, GPS location, lane information,and/or other data of, or associated with, the train. Additionally oralternatively, the telematics data may include one or more of, and notlimited to all of: time, braking, acceleration, left turn, right turn,heading, GPS (Global Positioning System) speed, GPS latitude andlongitude, gyroscope, battery level, and/or telephone usage informationor data of, or associated with, the train.

Train Telematics/Destination Device

In one aspect, a computer-implemented method of using train telematicsdata to reduce risk of collisions may be provided. The method mayinclude (1) receiving, via one or more autonomous vehicle processors(and/or associated transceivers), such as via wireless communication ordata transmission, train telematics data associated with movement of atrain directly from a train transceiver or indirectly from a smartrailroad crossing, the train telematics data including GPS location,speed, route, heading, acceleration, and/or track data; (2) determining,via the one or more autonomous vehicle processors, when, or a timeperiod of when, the train will pass through (or be passing through) arailroad crossing based upon the train telematics data (such as basedupon train GPS location, speed, heading, route, and/or trackinformation, and/or comparison with a GPS location of the railroadcrossing and a current time); (3) determining, via the one or moreautonomous vehicle processors, an alternate route for the autonomousvehicle to take to avoid waiting at the railroad crossing to allow forthe train to pass; and/or (4) directing, via the one or more autonomousvehicle processors, the autonomous vehicle to automatically travel alongthe alternate route, or alternatively directing the autonomous vehicleto automatically stop at the railroad crossing to allow the train topass unimpeded and to facilitate avoidance of train-vehicle collisions.

The method may include additional, less, or alternate actions, includingthose discussed elsewhere herein. For instance, the telematics data mayinclude data selected from one or more of, and not limited to all of: atimestamp; one or more sensor metrics indicative of braking motion ofthe train; one or more sensor metrics indicative of acceleration motionof the train; one or more sensor metrics indicative of cornering motionof the train; and one or more sensor metrics indicative of a directionof the train. The telematics data may include speed, acceleration,deceleration, GPS location, lane information, and/or other data of, orassociated with, the train. Additionally or alternatively, thetelematics data may include one or more of, and not limited to all of:time, braking, acceleration, left turn, right turn, heading, GPS (GlobalPositioning System) speed, GPS latitude and longitude, gyroscope,battery level, and/or telephone usage information or data of, orassociated with, the train.

The method may include adjusting or generating an insurance discount forvehicles having the risk mitigation or prevention functionalityassociated with receiving a wireless communication broadcast includingtrain telematics data, analyzing the train telematics data, anddirecting corrective actions based upon the train telematics data.

Train Telematics/Smart Railroad Crossing

In one aspect, a computer-implemented method of using train telematicsdata to reduce risk of collision may be provided. The method may include(1) receiving, via one or more smart railroad crossing processors(and/or associated transceivers), such as via wireless communication ordata transmission, train telematics data associated with movement of atrain directly from a train transceiver or indirectly from a smartrailroad crossing, the train telematics data including GPS location,speed, route, heading, acceleration, and/or track data; (2) determining,via the one or more processors, when the train will pass through (or atime period of when the train will be passing through) a railroadcrossing based upon the train telematics data (such as based uponcomparing train GPS location, speed, route, heading, and/or trackinformation with a GPS location of the railroad crossing and a currenttime); (3) determining, via the one or more processors, an alternateroute(s) for an autonomous vehicle(s) to take to avoid waiting at therailroad crossing while the train is passing through; and/or (4)broadcasting, via the one or more processors (and/or associatedtransceivers), a message to an autonomous vehicle(s) directing theautonomous vehicles to travel along an alternate route that completelyavoids the railroad crossing, or alternatively a message directing anautonomous vehicle(s) to automatically stop at the railroad crossingduring a predetermined time period to allow the train to pass unimpededto facilitate avoidance of train-vehicle collisions.

The method may include additional, less, or alternate actions, includingthose discussed elsewhere herein. For instance, the telematics data mayinclude data selected from one or more of, and not limited to all of: atimestamp; one or more sensor metrics indicative of braking motion ofthe train; one or more sensor metrics indicative of acceleration motionof the train; one or more sensor metrics indicative of cornering motionof the train; and one or more sensor metrics indicative of a directionof the train. The telematics data may include speed, acceleration,deceleration, GPS location, lane information, and/or other data of, orassociated with, the train. Additionally or alternatively, thetelematics data may include one or more of, and not limited to all of:time, braking, acceleration, left turn, right turn, heading, GPS (GlobalPositioning System) speed, GPS latitude and longitude, gyroscope,battery level, and/or telephone usage information or data of, orassociated with, the train.

The method may include adjusting or generating an insurance discount forvehicles having the risk mitigation or prevention functionalityassociated with receiving a wireless communication broadcast includingtrain telematics data, analyzing the train telematics data, anddirecting corrective actions based upon the train telematics data.

Exemplary System Configured to Use Train Telematics Data

As depicted by, and discussed in relation to, FIGS. 1, 2, and 6, forexample, in one aspect, a computer system configured to use traintelematics data to reduce risk of accidents may be provided. Thecomputer system may include at least one of one or more processors orassociated transceivers mounted on or within an autonomous orsemi-autonomous vehicle, the at least one of the one or more processorsor the associated transceivers configured to: (1) receive, via wirelesscommunication or data transmission, train telematics data associatedwith a train directly from a train transceiver or indirectly from arailroad crossing, the train telematics data including at least one ofGPS location, speed, route, heading, acceleration, or track data; (2)determine, based upon the train telematics data, (a) when, or a timeperiod of when, the train will pass through or be passing through therailroad crossing or another railroad crossing, or (b) when the train iswithin a predetermined distance of the railroad crossing or the otherrailroad crossing; (3) determine an alternate route for the autonomousvehicle to take to avoid waiting at the railroad crossing or the otherrailroad crossing to allow for the train to pass; and/or (4) directautonomous vehicle to one of (a) automatically travel along thealternate route, or (b) automatically stop at the railroad crossing orthe other railroad crossing to allow the train to pass unimpeded and tofacilitate avoidance of train-vehicle collisions and safer train andvehicle travel. The at least one of the one or more processors or theassociated transceivers may be configured to determine when, or the timeperiod of when, the train will pass through or be passing through therailroad crossing or the other railroad crossing based upon at least oneof (a) at least one of the GPS location, the speed, the heading, theroute, or the track data, or (b) comparison via the one or moreprocessors of the at least one of the GPS location, the speed, theheading, the route, or the track data with a GPS location of therailroad crossing or the other railroad crossing and a current time.

The computer system may be further configured to at least one ofdisplay, adjust, or generate an insurance discount for vehicles havingrisk mitigation or prevention functionality associated with receiving awireless communication broadcast including the train telematics data,analyzing the train telematics data, and directing corrective actionsbased upon the train telematics data, and/or a time or mileageusage-based insurance discount for vehicles based upon an amount ofusage of risk mitigation or prevention functionality associated withreceiving a wireless communication broadcast including the traintelematics data, analyzing the train telematics data, and directingcorrective actions based upon the train telematics data. The computersystem may be configured with additional, less, or alternatefunctionality, including that discussed elsewhere herein.

For instance, the train telematics data may include data selected fromone or more of, and not limited to all of: a timestamp; one or moresensor metrics indicative of braking motion of the train; one or moresensor metrics indicative of acceleration motion of the train; one ormore sensor metrics indicative of cornering motion of the train; and oneor more sensor metrics indicative of a direction of the train. The traintelematics data may include at least one of speed, acceleration,deceleration, GPS location, lane information, and/or other data of orassociated with, the train. The telematics data may include one or moreof, and not limited to all of: time, braking, acceleration, left turn,right turn, heading, GPS (Global Positioning System) speed, GPS latitudeand longitude, gyroscope, battery level, and/or telephone usageinformation or data of, or associated with, the train, and/or othertelematics and digital data, including that discussed elsewhere herein.

Exemplary Method of Using Train Telematics Data

As depicted by, and discussed in relation to, FIGS. 1, 2, and 6, forexample, in another aspect, a computer-implemented method of using traintelematics data to reduce risk of accidents may be provided. The methodmay include (1) receiving, via at least one of one or more autonomous(or semi-autonomous) vehicle processors or associated transceivers viawireless communication or data transmission, the train telematics dataassociated with a train directly from a train transceiver or indirectlyfrom a railroad crossing, the train telematics data including at leastone of GPS location, speed, route, heading, acceleration, or track data;(2) determining, via the one or more autonomous vehicle processors basedupon the train telematics data, (1) when, or a time period of when, thetrain will pass through or be passing through the railroad crossing oranother railroad crossing, or (2) when the train is within apredetermined distance of the railroad crossing or the other railroadcrossing; (3) determining, via the one or more autonomous vehicleprocessors, an alternate route for the autonomous vehicle to take toavoid waiting at the railroad crossing or the other railroad crossing toallow for the train to pass; and/or (4) directing, via the one or moreautonomous vehicle processors, the autonomous vehicle to one of (1)automatically travel along the alternate route, or (2) automaticallystop at the railroad crossing or the other railroad crossing to allowthe train to pass unimpeded and to facilitate avoidance of train-vehiclecollisions and safer train and vehicle travel. Determining, via the oneor more autonomous vehicle processors, when, or the time period of when,the train will pass through or be passing through the railroad crossingor the other railroad crossing based upon the train telematics data maybe based upon at least one of (1) at least one of the GPS location, thespeed, the heading, the route, or the track data, or (2) comparison viathe one or more autonomous vehicle processors of the at least one of theGPS location, the speed, the heading, the route, or the track data witha GPS location of the railroad crossing or the other railroad crossingand a current time.

The method may include at least one of displaying, adjusting orgenerating an insurance discount for vehicles having risk mitigation orprevention functionality associated with receiving a wirelesscommunication broadcast including the train telematics data, analyzingthe train telematics data, and directing corrective actions based uponthe train telematics data, and/or at least one of displaying, adjustingor generating a time or mileage usage-based insurance discount forvehicles based upon an amount of usage of risk mitigation or preventionfunctionality associated with receiving a wireless communicationbroadcast including the train telematics data, analyzing the traintelematics data, and directing corrective actions based upon the traintelematics data. The method may include additional, less, or alternatefunctionality, including that discussed elsewhere herein, and/or may beimplemented via one or more local or remote processors, transceivers,memory units, and other electronic componentry. The train telematicsdata may include the types of telematics data discussed elsewhereherein.

Exemplary System of Using Train Telematics Data

As depicted by, and discussed in relation to, FIGS. 1, 2, and 6, forexample, in one aspect, a system of using train telematics data toreduce risk of accidents may be provided. The system may include anautonomous (or semi-autonomous) vehicle with at least one of one or moreprocessors or transceivers configured to: (1) receive the traintelematics data associated with a train directly from a traintransceiver or indirectly from a railroad crossing, the train telematicsdata including at least one of GPS location, speed, route, heading,acceleration, or track data; (2) determine when the train will passthrough the railroad crossing or another railroad crossing based uponthe train telematics data; and/or (3) determine an alternate route forthe autonomous vehicle to take to avoid waiting at the railroad crossingor the other railroad crossing while the train is passing through tofacilitate avoidance of train-vehicle collisions and safer vehicle andtrain travel. Determining when the train will pass through the railroadcrossing or the other railroad crossing based upon the train telematicsdata may be based upon comparison via the one or more processors of atleast one of the GPS location, the speed, the route, the heading, or thetrack data with a GPS location of the railroad crossing or the otherrailroad crossing and a current time.

The autonomous vehicle may be further configured to: broadcast a messageto other autonomous vehicles that does one or more of (1) directs theother autonomous vehicles to travel along at least one alternate routethat completely avoids the railroad crossing or the other railroadcrossing, or (2) directs the other autonomous vehicles to automaticallystop at the railroad crossing or the other railroad crossing during apredetermined time period to allow the train to pass unimpeded tofacilitate avoidance of train-vehicle collisions. The system may befurther configured to at least one of display, adjust, or generate aninsurance discount for vehicles having risk mitigation or preventionfunctionality associated with receiving a wireless communicationbroadcast including the train telematics data, analyzing the traintelematics data, and directing corrective actions based upon the traintelematics data. The system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein, and the traintelematics data may include the types of telematics data discussedelsewhere herein.

Exemplary System Configured to Use Train Telematics Data

As depicted by, and discussed in relation to, FIGS. 1, 2, 7, and 8, forexample, in one aspect, a computer system configured to use traintelematics data to reduce risk of accidents via a mobile devicetraveling within a vehicle may be provided. The computer system mayinclude the mobile device having at least one of one or more processorsor transceivers, the at least one of the one or more processors or thetransceivers configured to: (1) receive, via wireless communication ordata transmission, train telematics data associated with a traindirectly from a train transceiver or indirectly from a railroadcrossing, the train telematics data including at least one of GPSlocation, speed, route, heading, acceleration, or track data; (2)determine when, or a time period of when, the train will pass through,be passing through, or be within a predetermined distance of therailroad crossing or another railroad crossing based upon the traintelematics data; (3) determine an alternate route for the vehicle totake to avoid waiting at the railroad crossing or the other railroadcrossing to allow for the train to pass unimpeded; and/or (4) cause thealternate route to be displayed on a display of the mobile device or avehicle navigation system to allow the train to pass unimpeded and tofacilitate avoidance of train-vehicle collisions. The at least one ofthe one or more processors or the transceivers may be configured todetermine when, or the time period of when, the train will pass through,be passing through, or be within the predetermined distance of therailroad crossing or the other railroad crossing based upon at least oneof (1) at least one of the GPS location, the speed, the heading, theroute, or the track data, or (2) comparison via the one or moreprocessors of the at least one of the GPS location, the speed, theheading, the route, or the track data with a GPS location of therailroad crossing or the other railroad crossing and a current time.

The system may be further configured to at least one of display, adjust,or generate an insurance discount for vehicles having risk mitigation orprevention functionality associated with receiving a wirelesscommunication broadcast including the train telematics data, analyzingthe train telematics data, and directing corrective actions based uponthe train telematics data, and/or a time or mile usage-based insurancediscount for vehicles based upon an amount of usage of risk mitigationor prevention functionality associated with receiving a wirelesscommunication broadcast including the train telematics data, analyzingthe train telematics data, and directing corrective actions based uponthe train telematics data. The system may include additional, less, oralternate functionality, including that discussed elsewhere herein, andthe train telematics data may include the types of telematics datadiscussed elsewhere herein.

Exemplary Method of Using Train Telematics Data

As depicted by, and discussed in relation to, FIGS. 1, 2, 7, and 8, forexample, in another aspect, a computer-implemented method of using traintelematics data to reduce risk of accidents via a mobile devicetraveling within a vehicle may be provided. The method may include (1)receiving, via at least one of one or more processors of the mobiledevice or associated transceivers via wireless communication or datatransmission, the train telematics data associated with a train directlyfrom a train transceiver or indirectly from a railroad crossing, thetrain telematics data including at least one of GPS location, speed,route, heading, acceleration, or track data; (2) determining, via theone or more processors of the mobile device based upon the traintelematics data, (1) when, or a time period of when, the train will passthrough or be passing through the railroad crossing or another railroadcrossing, or (2) when the train is within a predetermined distance ofthe railroad crossing or the other railroad crossing; (3) determining,via the one or more processors of the mobile device, an alternate routefor the vehicle to take to avoid waiting at the railroad crossing or theother railroad crossing to allow for the train to pass; and/or (4)causing, via the one or more processors of the mobile device, thealternate route to be displayed on a display of the mobile device or avehicle navigation system to allow the train to pass unimpeded and tofacilitate avoidance of train-vehicle collisions. Determining, via theone or more processors of the mobile device, when, or the time period ofwhen, the train will one of pass through, be passing through, or bewithin a predetermined distance of the railroad crossing or the otherrailroad crossing based upon the train telematics data may be based uponat least one of (1) at least one of the GPS location, the speed, theheading, the route, or the track data, or (2) comparison via the one ormore processors of the mobile device of the at least one of the GPSlocation, the speed, the heading, the route, or the track data with aGPS location of the railroad crossing or the other railroad crossing anda current time.

The method may include at least one of displaying, adjusting, orgenerating an insurance discount for vehicles having risk mitigation orprevention functionality associated with receiving a wirelesscommunication broadcast including the train telematics data, analyzingthe train telematics data, and directing corrective actions based uponthe train telematics data, and/or a time or mile usage-based insurancediscount for vehicles based upon an amount of usage of risk mitigationor prevention functionality associated with receiving a wirelesscommunication broadcast including the train telematics data, analyzingthe train telematics data, and directing corrective actions based uponthe train telematics data.

The foregoing method may include additional, less, or alternatefunctionality, including that discussed elsewhere herein, and may employthe types of telematics and/or digital data, and/or the Telematics App,discussed elsewhere herein. The foregoing method may be implemented viaone or more local or remote processors, transceivers, memory units, andother electronic componentry, and/or via computer-executableinstructions stored on non-transitory computer-readable media or medium.

Exemplary Method for Utilizing Train Telematics Data

As depicted by, and discussed in relation to, FIGS. 1, 2, 7, and 8, forexample, in another aspect, a computer-implemented method for utilizingtrain telematics data may be provided. The method may include (1)receiving, by a first mobile computing device located in a vehicle, thetrain telematics data from a second mobile computing device located on atrain, the train telematics data including information indicative of atleast one of a speed, a heading, or a location of the train; (2)determining, by the first mobile computing device, at least one of aspeed, a location, or a route of the vehicle; (3) determining, by thefirst mobile computing device based upon a comparison between (1) the atleast one of the speed, the location, or the route of the vehicle, and(2) the at least one of the speed, the heading, or the location of thetrain derived from the train telematics data, whether the vehicle willbe able to cross a railroad crossing before at least one of (1) acrossing signal associated with the railroad crossing is sounded or (2)the train is within a threshold distance from the railroad crossing;and/or (4) issuing at least one of an audible alarm or a visual alarmwhen it is determined by the first mobile computing device that thevehicle will not be able to cross the railroad crossing before the atleast one of (1) the crossing signal is sounded or (2) the train iswithin the threshold distance from the railroad crossing. The method mayinclude adjusting, by the first mobile computing device, a currentlycalculated driving route, when it is determined by the first mobilecomputing device that the vehicle will not be able to cross the railroadcrossing before the at least one of (1) the crossing signal is soundedor (2) the train is within the threshold distance from the railroadcrossing, wherein the adjusted route avoids the railroad crossing. Themethod may also or alternatively include receiving, by a smart railroadcrossing infrastructure, the train telematics data from the secondmobile computing device; and broadcasting, by the smart railroadcrossing infrastructure, the train telematics data received from thesecond mobile computing device so that the act of receiving, by thefirst mobile computing device, the train telematics data from the secondmobile computing device comprises receiving, by the first mobilecomputing device, the train telematics data from the second mobilecomputing device via the smart railroad crossing infrastructure.

The foregoing method may include additional, less, or alternatefunctionality, including that discussed elsewhere herein, and may employthe types of telematics and/or digital data, and/or the Telematics App,discussed elsewhere herein. The foregoing method may be implemented viaone or more local or remote processors, transceivers, memory units, andother electronic componentry, and/or via computer-executableinstructions stored on non-transitory computer-readable media or medium.

Additional Considerations

With the foregoing, an insurance customer may opt-in to a rewards,insurance discount, or other type of program. After the insurancecustomer provides their affirmative consent, an insurance providertelematics application and/or remote server may collect telematicsand/or other data (including image or audio data) associated withinsured assets, including before, during, and/or after aninsurance-related event or vehicle collision. In return, risk-aversedrivers, and/or vehicle owners may receive discounts or insurance costsavings from the insurance provider.

In one aspect, telematics data, and/or other data, including the typesof data discussed elsewhere herein, may be collected or received by aninsured's mobile device or smart vehicle, a Telematics App (includingthose discussed herein), and/or an insurance provider remote server,such as via direct or indirect wireless communication or datatransmission from a Telematics App running on the insured's mobiledevice, after the insured or customer affirmatively consents orotherwise opts-in to an insurance discount, reward, or other program.The insurance provider may then analyze the data received with thecustomer's permission to provide benefits to the customer. As a result,risk-averse customers may receive insurance discounts or other insurancecost savings based upon data that reflects low risk driving behaviorand/or technology that mitigates or prevents risk to insured assets,such as vehicles or even homes, and/or (ii) vehicle operators orpassengers.

Although the disclosure provides several examples in terms of twovehicles, two mobile computing devices, two on-board computers, onetrain, etc., aspects include any suitable number of computing devices,vehicles, trains, etc. For example, aspects include an externalcomputing device receiving telematics data and/or geographic locationdata from a large number of computing devices (e.g., 100 or more mobilecomputing devices), and issuing alerts to those computing devices inwhich the alerts are relevant in accordance with the various techniquesdescribed herein.

Although the foregoing text sets forth a detailed description ofnumerous different embodiments, it should be understood that the legalscope of the description is defined by the words of the claims set forthat the end of this patent and equivalents. The detailed description isto be construed as exemplary only and does not describe every possibleembodiment since describing every possible embodiment would beimpractical. Numerous alternative embodiments may be implemented, usingeither current technology or technology developed after the filing dateof this patent, which would still fall within the scope of the claims.

The following additional considerations apply to the foregoingdiscussion. Throughout this specification, plural instances mayimplement components, operations, or structures described as a singleinstance. Although individual operations of one or more methods areillustrated and described as separate operations, one or more of theindividual operations may be performed concurrently, and nothingrequires that the operations be performed in the order illustrated.Structures and functionality presented as separate components in exampleconfigurations may be implemented as a combined structure or component.Similarly, structures and functionality presented as a single componentmay be implemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (e.g., code embodiedon a machine-readable medium or in a transmission signal) or hardware.In hardware, the routines, etc., are tangible units capable ofperforming certain operations and may be configured or arranged in acertain manner. In example embodiments, one or more computer systems(e.g., a standalone, client or server computer system) or one or morehardware modules of a computer system (e.g., a processor or a group ofprocessors) may be configured by software (e.g., an application orapplication portion) as a hardware module that operates to performcertain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC)) toperform certain operations. A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. Considering embodiments inwhich hardware modules are temporarily configured (e.g., programmed),each of the hardware modules need not be configured or instantiated atany one instance in time. For example, where the hardware modulescomprise a general-purpose processor configured using software, thegeneral-purpose processor may be configured as respective differenthardware modules at different times. Software may accordingly configurea processor, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules may provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multipleof such hardware modules exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the hardware modules. In embodiments in whichmultiple hardware modules are configured or instantiated at differenttimes, communications between such hardware modules may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware modules have access. Forexample, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and may operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processor-implemented. For example, at least some of theoperations of a method may be performed by one or more processors orprocessor-implemented hardware modules. The performance of certain ofthe operations may be distributed among the one or more processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processor or processors,and/or processor-implemented modules, may be located in a singlelocation (e.g., within a vehicle environment, a train environment, aninfrastructure component, a home environment, an office environment oras a server farm), while in other embodiments the processor(s) and/orprocessor-implemented modules may be distributed across a number oflocations.

The patent claims at the end of this patent application are not intendedto be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s).

This detailed description is to be construed as exemplary only and doesnot describe every possible embodiment, as describing every possibleembodiment would be impractical, if not impossible. One may implementnumerous alternate embodiments, using either current technology ortechnology developed after the filing date of this application.

What is claimed:
 1. A computer system configured to use train telematicsdata to reduce accident risk, the computer system comprising: a mobiledevice traveling within a vehicle, the mobile device including: at leastone processor or associated transceiver, the at least one processor orassociated transceiver configured to: receive, at the mobile device viawireless communication or data transmission, the train telematics dataassociated with a train, the train telematics data including locationand speed data; determine, at the mobile device based upon the traintelematics data, an indication of when the train will pass through arailroad crossing; determine, at the mobile device based upon arelevance of the train, an alternate route for the vehicle to take toavoid waiting at the railroad crossing to allow for the train to passthrough the railroad crossing, the relevance of the train being basedupon the indication of when the train will pass through or be within apredetermined distance of the railroad crossing; and cause, based uponthe relevance of the train, the mobile device or a vehicle navigationsystem to provide a graphical user interface (GUI) including a displayof (i) an indication that the train will pass through the railroadcrossing and (ii) the alternate route, to facilitate the train safelypassing through the railroad crossing.
 2. The computer system of claim1, wherein the vehicle is an autonomous vehicle, and at least oneprocessor is configured to determine an alternate route for theautonomous vehicle to take to avoid waiting at the railroad crossing. 3.The computer system of claim 2, wherein the telematics data associatedwith the vehicle includes at least one of location, acceleration,deceleration, braking, cornering, direction, heading, left turn, rightturn, speed, lane, or gyroscope data associated with the vehicle.
 4. Thecomputer system of claim 1, wherein the at least one processor orassociated transceiver is configured to determine the indication of whenthe train will pass through the railroad crossing based upon at leastone of (1) at least one of the location data or speed data, or (2)comparison via the one or more processors of (i) the at least one of thelocation data or speed data with (ii) at least one of a current time orlocation data of one of the railroad crossing.
 5. The computer system ofclaim 1, wherein the train telematics data further includes one or moreof time, braking, cornering, direction, heading, left turn, right turn,track, GPS (Global Positioning System) latitude and longitude,gyroscope, battery level, or telephone usage data associated with thetrain.
 6. The computer system of claim 1, further comprising aninsurance provider remote server, wherein the at least one processor orassociated transceiver is configured to send an indication to theinsurance provider remote server that the mobile device traveling withinthe vehicle includes risk mitigation or prevention functionalityassociated with (1) receiving the train telematics data, and (2)directing corrective actions based upon the relevance of the train, soas to cause the insurance provider remote server to at least one ofdisplay, adjust, or generate an insurance discount associated with thevehicle.
 7. The computer system of claim 6, wherein the at least oneprocessor or associated transceiver is configured to send an indicationof an amount of usage of the risk mitigation or prevention functionalityto the insurance provider remote server so as to cause the insuranceprovider remote server to at least one of display, adjust, or generatethe insurance discount as a time or mileage usage-based insurancediscount.
 8. A computer-implemented method of using train telematicsdata to reduce accident risk, the method comprising: receiving, at amobile device traveling within a vehicle via at least one processor ofthe mobile device or associated transceiver via wireless communicationor data transmission, the train telematics data associated with a train,the train telematics data including location and speed data;determining, at the mobile device via the at least one processor of themobile device based upon the train telematics data, an indication ofwhen the train will pass through a railroad crossing; determining, atthe mobile device via the at least one processor of the mobile device,based upon a relevance of the train, an alternate route for the vehicleto take to avoid waiting at the railroad crossing to allow for the trainto pass through the railroad crossing, the relevance of the train beingbased upon the indication of when the train will pass through therailroad crossing; and causing, via the at least one processor of themobile device, based upon the relevance of the train, the mobile deviceor a vehicle navigation system to provide a graphical user interface(GUI) including a display of (i) an indication that the train will passthrough the railroad crossing and (ii) the alternate route, tofacilitate the train safely passing through the railroad crossing. 9.The computer-implemented method of claim 8, the method comprisingdetermining, via the at least one processor of the mobile device, therelevance of the train by determining, based upon the indication of whenthe train will pass through the railroad crossing, and further basedupon telematics data associated with the vehicle, an indication ofwhether the vehicle will be able to drive through the railroad crossingwithout the train being within a threshold distance from the railroadcrossing.
 10. The computer-implemented method of claim 8, wherein thevehicle is an autonomous vehicle, and the method further comprisesdetermining, via the at least one processor of the mobile device, analternate route for the autonomous vehicle to take to avoid waiting atthe railroad crossing.
 11. The computer-implemented method of claim 8,wherein determining, via the at least one processor of the mobiledevice, the indication of when the train will pass through the railroadcrossing is based upon at least one of (1) at least one of the locationdata or speed data, or (2) comparison of (i) the at least one of thelocation data or the speed data with (ii) at least one of a current timeor location data of one of the railroad crossing.
 12. Thecomputer-implemented method of claim 8, wherein the train telematicsdata includes one or more of time, braking, cornering, direction,heading, left turn, right turn, track, GPS (Global Positioning System)latitude and longitude, gyroscope, battery level, or telephone usagedata associated with the train.
 13. The computer-implemented method ofclaim 8, the method comprising sending, via the at least one processorof the mobile device or the associated transceiver, an indication to aninsurance provider remote server that the mobile device traveling withinthe vehicle includes risk mitigation or prevention functionalityassociated with (1) receiving the train telematics data, and (2)directing corrective actions based upon the relevance of the train, soas to cause the insurance provider remote server to at least one ofdisplay, adjust, or generate an insurance discount associated with thevehicle.
 14. The computer-implemented method of claim 13, the methodcomprising sending, via the at least one processor of the mobile deviceor the associated transceiver, an indication of an amount of usage ofthe risk mitigation or prevention functionality to the insuranceprovider remote server so as to cause the insurance provider remoteserver to at least one of display, adjust, or generate the insurancediscount as a time or mileage usage-based insurance discount.
 15. Acomputer-implemented method for utilizing train telematics data, themethod comprising: receiving, by a first device located within avehicle, the train telematics data from a second device associated witha train, the train telematics data including information indicative of alocation and speed of the train; determining, by the first devicelocated within the vehicle, at least one of a speed, a location, or aroute of the vehicle; determining, by the first device located withinthe vehicle, whether the vehicle will be able to cross a railroadcrossing before the train is within a threshold distance from therailroad crossing, so as to determine a relevance of the train; andproviding, within the vehicle, a graphical user interface (GUI)including a display of (1) an indication of whether the vehicle will beable to cross the railroad crossing before the train is within thethreshold distance from the railroad crossing, and (2) an indication ofthe location of the train, to facilitate the train passing through therailroad crossing unimpeded by the vehicle.
 16. The computer-implementedmethod of claim 15, wherein determining, by the first device locatedwithin the vehicle, whether the vehicle will be able to cross therailroad crossing is based upon a comparison between (1) the at leastone of the speed, the location, or the route of the vehicle, and (2) thelocation and speed of the train.
 17. The computer-implemented method ofclaim 15, the method comprising determining, based upon a currentdriving route, an adjusted driving route for the vehicle when it isdetermined that the vehicle will not be able to cross the railroadcrossing before the train is within the threshold distance from therailroad crossing.
 18. The computer-implemented method of claim 15, themethod comprising: receiving, by a smart railroad crossinginfrastructure, the train telematics data from the second device; andbroadcasting, by the smart railroad crossing infrastructure, the traintelematics data so that the act of receiving, by the first device, thetrain telematics data from the second device includes receiving, by thefirst device, the train telematics data from the second device via thesmart railroad crossing infrastructure.
 19. The computer-implementedmethod of claim 15, wherein the vehicle is an autonomous vehicle, andthe method further comprises determining, via the first device, analternate route for the autonomous vehicle to take to avoid waiting atthe railroad crossing.
 20. The computer-implemented method of claim 15,the method comprising sending, by the first device located within thevehicle, an indication to an insurance provider remote server that thefirst device located within the vehicle includes risk mitigation orprevention functionality associated with (1) receiving the traintelematics data, and (2) directing corrective actions based upon therelevance of the train, so as to cause the insurance provider remoteserver to at least one of display, adjust, or generate an insurancediscount associated with the vehicle.